Research on Grain Production Services in the Hexi Corridor Based on the Link Relationship of “Water–Soil–Carbon–Grain”

Abstract

Elucidating the trade-offs and synergies among ecosystem services is crucial for effective ecosystem management and the promotion of sustainable development in specific regions. The Hexi Corridor, a vital agricultural hub in Northwest China, is instrumental in both ecological conservation and socioeconomic advancement throughout the area. Utilizing an integrated “water–soil–carbon–grain” framework, this study conducted a quantitative assessment of four essential ecosystem services within the Hexi Corridor from 2000 to 2020: water yield, soil conservation, vegetation carbon sequestration, and grain production. Our research thoroughly explores the equilibrium and synergistic interactions between grain production and other ecosystem services, while also exploring potential strategies to boost grain yields through the precise management of these services. The insights garnered are invaluable for strategic regional development and will contribute to the revitalization efforts in Northwest China. Key findings include the following: (1) between 2000 and 2020, grain production exhibited a steady increase, alongside rising trends in water yields, soil conservation, and carbon sequestration, all of which demonstrated significant synergies with agricultural productivity; (2) in areas identified as grain production hotspots, there were stronger positive correlations between grain output and carbon sequestration services, soil conservation, and water yields than the regional averages, suggesting more pronounced mutual benefits; (3) the implementation of strategic initiatives such as controlling soil erosion, expanding afforestation efforts, and enhancing water-saving irrigation infrastructure could simultaneously boost ecological services and agricultural productivity. These results significantly enhance our comprehension of the interplay between ecosystem services in the Hexi Corridor and present practical approaches for the optimization of regional agricultural systems.

1. Introduction

In the contemporary context of global climate change, geopolitical turmoil—exemplified by the Russia–Ukraine conflict—and the economic repercussions of the pandemic, the problem of global food insecurity has escalated to unprecedented levels. This crisis poses a formidable obstacle to the accomplishment of the 2030 Sustainable Development Goals [1]. In Gansu Province, Northwestern China, the Hexi Corridor is identified as a pivotal agricultural zone, playing a strategic role in regional socioeconomic stability through its grain production capabilities [2]. This region is characterized by three major inland river systems—the Shiyang, Heihe, and Shule—which support distinct oasis irrigation areas that underpin local agricultural productivity [3]. These oasis ecosystems are crucial, providing vital food production services that are intimately connected with key ecosystem functions such as water conservation, carbon sequestration in vegetation, and soil retention [4]. To augment agricultural productivity and efficiency, it is essential to undertake a systematic exploration of the intricate interrelationships between food production and other ecosystem services. By elucidating their synergistic benefits, underlying mechanisms, and functional utility, strategies can be formulated to enhance the regional grain output while promoting sustainable development [5].

In the research field exploring the relationship between grain production and ecosystem services, the global academic community has conducted multidimensional investigations. For example, in West Bengal, India, an ecosystem integrating crops, fruit trees, and forest trees has been established on gully-degraded land. This not only reduces soil erosion and promotes a variety of beneficial ecosystem services but also increases crop yields [6]. Elisabeth et al. found that the restoration of semi-natural grasslands in Western Estonia can enhance biodiversity and improve ecosystem services, which is conducive to increasing the food supply [7]. In the major rice-producing areas of Taiwan, China, Lin et al. evaluated and visualized land use, soil properties, and the ecosystem service status and found a positive correlation between regulatory services and crop productivity [8]. From the perspective of methodological tools, the InVEST model, an ecological assessment tool jointly developed by Stanford University, The Nature Conservancy (TNC), and the World Wildlife Fund (WWF) [9], has been validated for its applicability in many parts of the world. For instance, it has been used in the urbanized rainforest and Guinean savanna ecological zones of Nigeria to assess the status of ecosystem regulatory services [10], in Sri Lanka to simulate soil erosion and sedimentation in catchments near proposed tropical reservoirs to guide policy formulation [11], and in Dalian to evaluate the spatiotemporal evolution of carbon storage [12]. The current global agricultural research covers natural factors, socioeconomic impacts, and technical strategies [13,14]. However, there is a common gap: the application of the InVEST model in arid regions mostly focuses on single ecosystem services (such as water production or carbon sequestration), while quantitative research on the synergy among multiple elements of the “water–soil–carbon–grain” nexus remains relatively weak. This gap is prevalent in arid regions worldwide, and the case of the Hexi Corridor in China can provide supplementary insights to address it.

The uniqueness of the Hexi Corridor makes it an ideal case to fill the aforementioned research gap: cultivated land in this region accounts for only 5% of its total land area, yet it needs to support a population of 4.402 million. This agricultural challenge is exacerbated by the region’s arid conditions, which make grain production particularly demanding. The inherent conflict between ensuring food security and maintaining ecological balance in arid and semi-arid regions has long been a focal point of scholarly investigation. Recent studies have provided important insights into this complex dynamic. Luo et al. evaluated the trade-offs between grain production and other ecosystem services in Xinjiang’s Tacheng Emin Basin, revealing distinct compromises required for sustainability. Their study found that, as the grain production service increases from low to high, its relationship with other services shows a changing trend of “trade-off–synergy–trade-off” [15]. In contrast, Dai et al. identified synergistic relationships among provisioning services (water and grain production), regulating services (such as sandstorm prevention and net primary productivity, NPP), and supporting services (including biodiversity conservation) on the Qinghai–Tibet Plateau, facilitated by ecological engineering interventions. Sustainable ecosystem management following the implementation of ecological engineering projects may benefit future contributions to SDG realization [16]. Unlike the regional characteristics of the Emin Basin in Tacheng, Xinjiang—where grain production services are primarily in a trade-off relationship with other ecosystem services [15]—and the Qinghai–Tibet Plateau, where “synergy is driven by ecological engineering” [16], the oasis agriculture in the Hexi Corridor relies on artificial irrigation systems. The “water–soil–carbon–grain” relationship here is more significantly influenced by human activities, and it can serve as a reference for irrigated agricultural areas worldwide.

In summary, this study takes grain production services as the starting point, with the overarching goal of improving these services. Employing the InVEST model, this research quantitatively evaluates ecosystem services such as water production, soil conservation, vegetation carbon sequestration, and food production in the Hexi Corridor. It analyzes the trade-offs and synergies among these services and conducts a hotspot analysis of food production services. Finally, recommendations for the improvement of grain production in this region are put forward.

2. Materials and Methods

2.1. Study Area

The Hexi Corridor, located in Northwestern Gansu Province, spans the coordinates 37°17′–42°48′ N, 92°12′–103°48′ E. This region serves as a transitional zone between the northeastern margin of the Qinghai–Tibet Plateau and the Badain Jaran Desert. The area is geographically distinguished by its corridor-like topography west of the Yellow River and is colloquially known as the “Granary of Northwest China”. It covers approximately 240,000 hectares and extends about 1000 km from east to west, with a variable width that reaches nearly 200 km at its widest and narrows considerably at certain points. The Hexi Corridor includes five prefecture-level cities within Gansu Province: Wuwei, Jinchang, Zhangye, Jiuquan, and Jiayuguan (Figure 1).

The climate of the Hexi Corridor is predominantly temperate to warm–temperate and continental arid [17]. While some southern areas of the corridor receive annual precipitation exceeding 300 mm, the majority of the region receives less than 200 mm, exhibiting a pronounced decreasing gradient from east to west [18]. This scarcity of precipitation, coupled with annual evaporation rates often surpassing 2000 mm, categorizes the region as hyper-arid according to the UNESCO classification standards [19]. The area records mean annual temperatures ranging between 4 °C and 10 °C, accompanied by significant diurnal temperature variations averaging 15 °C. These conditions are mitigated by the presence of abundant sunshine, which provides between 2600 and 3250 h of illumination annually, fostering favorable photothermal conditions despite the arid climate [20]. Hydrologically, the region relies on an inland drainage system from the Qilian Mountains, supported by orographic precipitation (300–500 mm annually at higher elevations), glacial meltwater, and groundwater recharge [21]. The primary hydrological network comprises three parallel river basins—the Shiyang in the east, the Heihe in the center, and the Shule in the west—which together drain an area of 225,900 km² and generate annual runoff of 3.937 billion m³ [22]. The soil distribution in the Hexi Corridor exhibits a distinct longitudinal pattern. The eastern region is dominated by gray desert soil, light brown calcareous soil, and gray calcareous soil, while the central area features gray-brown desert soils, and the western sector is characterized by brown desert soils [23]. This pedological diversity reflects the climatic gradient across the region. The landscape of the Hexi Corridor comprises a complex mosaic of desert and Gobi ecosystems, which cover approximately 60% of the total area, alongside fluvial oasis systems (about 5%) and alluvial plains. The linear oasis ecosystems along the river systems, albeit constituting less than 5% of the land area, support over 90% of the agricultural production through intensive irrigation. This extreme spatial concentration of agricultural productivity highlights the critical importance of efficient water resource management, precision irrigation practices, and the conservation of oasis ecosystems. These strategies are essential in maintaining regional food security and achieving sustainable development in this fragile arid environment, thereby addressing the dual challenges of increasing agricultural outputs and preserving ecological balance [2].

2.2. Data Sources

This research utilized integrated multi-source remote sensing datasets and statistical records. All spatial data were standardized to a 1 km resolution using interpolation techniques and were projected in the WGS 1984 coordinate reference system (EPSG: 4326). The comprehensive list of data sources and their specifications is detailed in

Table 1. Data sources.

Data Type	Data Source and Processing
Land use data	Resources and Environment Science Data Center of Chinese Academy of Sciences (http://www.resdc.cn/ (accessed on 4 June 2024)), including land use data from 2000, 2005, 2010, 2015, and 2020 at 1 km spatial resolution
Soil data	World Soil Database (HWSD), Chinese soil dataset, 1 km spatial resolution
Bedrock depth data	National Oceanic and Atmospheric Administration of the United States (https://www.ncei.noaa.gov/ (accessed on 6 June 2024)), 1 km spatial resolution
DEM data	Geospatial Data Cloud (http://www.gscloud.cn/ (accessed on 20 June 2024)), 1 km spatial resolution
NDVI data	Geospatial Data Cloud (https://www.gscloud.cn/ (accessed on 27 June 2024)), ASTER GDEM 30 m resolution digital elevation data
Rainfall data	China Meteorological Data Network (http://data.cma.cn/ (accessed on 14 July 2024)), station data processed using ANUSPLIN interpolation, 1 km spatial resolution
Potential evapotranspiration data	China Meteorological Data Network (http://data.cma.cn/ (accessed on 14 July 2024)), station data calculated using the Modified Hargreaves formula [24], includes daily maximum and minimum temperatures and daily radiation, 1 km spatial resolution
Statistical data	Statistical Yearbook and Water Resources Bulletin of Gansu Province from 2000 to 2020 (https://tjj.gansu.gov.cn/ (accessed on 3 December 2024) and https://slt.gansu.gov.cn/ (accessed on 3 December 2024))

.

2.3. Research Methods

2.3.1. Measurement of Ecosystem Services

The Hexi Corridor, characterized by its arid land features, including water scarcity (annual precipitation less than 200 mm), severe soil erosion, and fragile ecosystems, poses significant limitations on the grain production capacity. To systematically evaluate these constraints, four key ecosystem services were quantified: (1) water yields, (2) soil retention, (3) vegetation carbon sequestration, and (4) grain production. The four selected services—water production, soil retention, carbon sequestration, and grain production—are directly linked to these regional priorities: water production corresponds to the critical role of ecosystems in regulating water resources; soil retention helps to mitigate desertification risks; carbon sequestration reflects the region’s potential in climate regulation; and grain production service corresponds to the research objective. The assessments employed two InVEST model modules—specifically, the hydrological and sediment delivery ratio (SDR) modules—for the estimation of water yields and soil retention [25]. Vegetation productivity was analyzed using the Carnegie–Ames–Stanford Approach (CASA) model to derive the NPP as an indicator of the carbon sequestration capacity [26]. Grain production services were estimated through established NDVI–crop yield linear regression models, which capture the relationship between vegetation vigor and agricultural productivity [27,28,29].

(1)

Estimation of Water Production Services

The quantification of water yield services was performed using the Water Yield module of the InVEST model, which applies the Budyko hydroclimatological framework [30]. This methodology computes the grid-level water yield by determining the difference between precipitation and actual evapotranspiration (AET), in accordance with the fundamental water balance equation:

$$Y_{xj}=(1-{\displaystyle \frac{{AET}_{xj}}{P_{xj}}}) P_x$$

(1)

In this equation, $Y_{xj}$ represents the annual water production for pixel x of land use type j, expressed in millimeters. $P_x$ denotes the annual precipitation at pixel x (in mm). The annual actual evapotranspiration (mm) for land use type j at pixel x for ${AET}_{xj}$ is calculated using

$${\displaystyle \frac{{AET}_{xj}}{P_x}}={\displaystyle \frac{1+{\omega }_x{R}_{xj}}{1+{\omega }_x{R}_{xj}+1/R_{xj}}}$$

(2)

Here, $R_{xj}$ is the dimensionless dryness index for grid x on land use type j, signifying the ratio of potential evaporation to rainfall. ${\omega }_x$ indicates the effective water content of plants in grid x. The methodologies for the derivation of biophysical tables and pertinent parameters are adapted from various studies [8,31,32].

(2)

Estimation of Soil Conservation Services

The capacity for soil conservation is indicative of the ecosystem’s role in preventing soil erosion through vegetative cover, such as forests and grassland, which is essential in combating regional land degradation. The InVEST model assesses this service using an advanced SDR method grounded in the Revised Universal Soil Loss Equation (RUSLE) framework [33]. This algorithm incorporates multiple biophysical factors:

$$S_i=R_i{K}_i{LS}_i·{SDR}_{bare\_i}$$

(3)

$$E_i=R_i{K}_i{LS}_i{C}_i{P}_i·{SDR}_i$$

(4)

$${SR}_i=S_i-E_i$$

(5)

Within these formulas, $S_i$, $E_i$, and ${SR}_i$ represent the potential sand content, actual sand content, and soil conservation at grid cell x, respectively. $R_i$ is the rainfall erosion coefficient for grid unit x; $K_i$ denotes the soil erodibility factor for grid unit x; ${LS}_i$ is the slope length and gradient factor at grid cell x; $C_i$ is the crop management factor at grid unit x; $P_i$ is the support practice factor at grid cell x; ${SDR}_{bare\_i}$ is the sediment transport ratio under bare soil conditions at grid unit x; ${SDR}_i$ reflects the sediment transport ratio under vegetative cover and soil and water conservation measures at grid cell x. The calculation methods for R and K are derived from the studies by Qin et al. [33] and the application of the Erosion Productivity Impact Calculator (EPIC) formula by Fu et al. [34], respectively. The estimations for L and S are conducted using InVEST models, drawing on the research by Sun [31].

(3)

Estimation of Vegetation Carbon Sequestration Services

The capacity for carbon sequestration by vegetation was assessed utilizing the NPP, derived from the CASA model [35]. The calculation of the NPP incorporates the efficiency of photosynthetically active radiation utilization, as expressed by the following equation:

$$NPP\left(x,t\right)=APAR(x,t)\times \epsilon (x,t)$$

(6)

In this equation, $NPP\left(x,t\right)$ denotes the NPP (g/m²) of vegetation in pixel $x$ during month $t$, $APAR(x,t)$ represents the photosynthetically active radiation absorbed by pixel $x$ during month $t$ (MJ/m²), and $\epsilon (x,t)$ indicates the actual light energy utilization efficiency (g/MJ) of pixel $x$ during month $t$.

Vegetation photosynthesis plays a crucial role in carbon–oxygen conversion within terrestrial ecosystems. Utilizing stoichiometric principles, the carbon sequestration capacity in the Hexi Corridor was estimated from the total vegetation NPP using established conversion factors: 1.63 kg of CO₂ fixation per 1 kg of organic matter production, with carbon content of 27% in CO₂ [36]. This relationship facilitated the following computation of carbon sequestration:

$$W_C=1.63\times 0.27\times NPP\times A$$

(7)

Here, $W_C$ symbolizes the annual carbon sequestration by vegetation (t/a); NPP refers to the NPP of a forest stand (t km⁻² a⁻¹); and A denotes the forest area (km²).

(4)

Estimation of Grain Production Services

Grain production is identified as a vital ecosystem provisioning service, primarily derived from cultivated land. Building on previous research that demonstrates a robust linear correlation between the NDVI and crop yield [27,28,29], this study utilizes NDVI values from cultivated land as spatial allocation weights for the estimation of grain production. The pixel-level estimation is encapsulated in the equation below:

$${GP}_i={\displaystyle \frac{{NDVI}_i}{{NDVI}_{sum}}}\times GP$$

(8)

In this equation, ${GP}_i$ represents the grain yield of grid i, ${NDVI}_i$ is the NDVI value of grid i, ${NDVI}_{sum}$ is the cumulative NDVI of cultivated land in the Hexi Corridor region, and GP is the total grain yield of the Hexi Corridor region.

2.3.2. Analysis of Ecosystem Trade-Offs and Synergies

This study applies Pearson correlation analysis to quantify the relationships between paired ecosystem services, using the correlation coefficient (r) as a metric to identify either trade-offs (negative correlations) or synergies (positive correlations) [37]. The statistical methodology is detailed as follows:

$$Z_{xy}={\displaystyle \frac{\sum _{i=1}^n(x_i-\overline{x})(y_i-\overline{y})}{\sqrt{\sum _{i=1}^n{(x_i-\overline{x})}^2\sum _{i=1}^n{(y_i-\overline{y})}^2}}}$$

(9)

In this formula, $x_i$ and $y_i$ are the i-th values of variables x and y, respectively, while $\overline{x}$ and $\overline{y}$ represent the average values of these variables. The Pearson correlation coefficient ranges within [−1, 1]. A positive $Z_{xy}>0$ implies a synergistic relationship between the two services; a negative $Z_{xy}<0$ indicates a trade-off. Based on the significance test, correlations were further classified: a p-value less than 0.05 was considered strongly significant, and values between 0.05 and 0.1 were deemed weakly significant. Moreover, a $Z_{xy}$ of 0 or p greater than 0.1 suggests either a non-significant relationship or an unclear relationship between the two ecosystem services [38].

2.3.3. Conversion of Land Use

The land use transition matrix effectively represents the dynamic processes of land use transformation over various periods within the study area [39]. The matrix is defined by the following equation:

$$\mathit{S}=\left[\begin{array}{cccc}{S}_{11}& S_{12}& \dots & S_{1n}\\ S_{21}& S_{22}& \dots & S_{2n}\\ \dots & \dots & \dots & \dots \\ S_{n1}& S_{n2}& \dots & S_{nn}\end{array}\right]$$

(10)

In this equation, $S_{ij}$ denotes the area transferred from the i-th land use type to the j-th type, and n represents the total number of land use categories.

2.3.4. Coldspot and Hotspot Analysis

Coldspot and hotspot analysis is a robust spatial clustering method used to detect statistically significant concentrations of high-value (hotspots) and low-value (coldspots) phenomena within a geographic area. This study utilizes the Getis-Ord Gi* statistic, as implemented in ArcGIS Pro (version 3.1), to measure spatial autocorrelation using standardized z-scores and corresponding p-values [40]. The analytical model is expressed through the following equations:

$$G_i^{\ast }\left(d\right)={\displaystyle \frac{\sum _j^n{W}_{ij}\left(d\right)X_j}{\sum _j^{n}X}}$$

(11)

$$Z\left(G_i^{\ast }\right)={\displaystyle \frac{G_i^{\ast }-E\left(G_i^{\ast }\right)}{\sqrt{Var\left(G_i^{\ast }\right)}}}$$

(12)

In these formulations, E($G_i^{\ast }$) represents the expected mathematical value of $G_i^{\ast }$; Var($G_i^{\ast }$) denotes the coefficient of variation for $G_i^{\ast }$; and $W_{ij}\left(d\right)$ signifies the spatial weight. When $Z\left(G_i^{\ast }\right)$ < 0, it suggests that the surrounding values are below the average, indicating the clustering of lower values and thereby defining the area as a coldspot. Conversely, when $Z\left(G_i^{\ast }\right)$ > 0, it suggests that the surrounding values exceed the average, indicating the clustering of higher values and defining the area as a hotspot [41]. In this context, the distribution of grain-producing areas in the Hexi Corridor region is notably concentrated. Consequently, a coldspot and hotspot analysis was conducted on its grain production services. Subsequently, an analysis of the balance and collaborative relationships within the hotspot areas was performed to explore strategies aimed at enhancing grain production.

3. Result

3.1. Analysis of Spatiotemporal Distribution Characteristics of Different Ecosystem Services

The analysis of the spatiotemporal patterns of ecosystem services in the Hexi Corridor from 2000 to 2020 reveals distinct characteristics in the distribution and dynamics of the water yield (Figure 2). The services related to water production demonstrate pronounced spatial heterogeneity, with consistently elevated values (15–28 mm/y) concentrated in the Southern Qilian Mountains region, gradually diminishing northward to minimal yields (<5 mm/y) in the arid plains. This spatial pattern reflects the strong orographic influence on precipitation distribution across the region. Temporally, water production has shown significant interannual variability, culminating in a peak in 2010, with a regional mean of 2.26 mm—a 94.8% increase from the 2000 level of 1.16 mm—followed by a sharp 46.9% decrease to 1.20 mm by 2020. Subregional analysis reveals notable deviations in water yield patterns, with the Shule River headwaters exhibiting 37% above-average production during 2005–2010, while the Shiyang River basin recorded a 42% higher-than-average yield in 2020. These spatial and temporal variations in water production are strongly correlated with recorded precipitation anomalies in the Qilian Mountains [42], indicating that climate variability is the primary driver. The observed gradient in the water yield from south to north highlights the critical hydrological functions of the mountainous southern areas, while the substantial interannual fluctuations underline the vulnerability of water provisioning services to climatic changes in this arid region. These findings underscore the importance of mountain ecosystems in sustaining regional water security and the necessity of incorporating climate-induced variability into water resource management strategies.

Soil conservation services play an indispensable role in sustaining agricultural productivity in the Hexi Corridor, displaying distinct spatiotemporal patterns from 2000 to 2020. The capacity for soil conservation exhibited a fluctuating trend, initially increasing and then decreasing, peaking in 2010 at 1716 tons/km², marking a 17.2% rise from 2000 (1464 tons/km²). This capacity subsequently declined by 12.6% to 1500 tons/km² during 2010–2015, before experiencing a modest rebound of 2.5% to 1538 tons/km² in 2015–2020. Spatially, the distribution maintained a consistent pattern, with higher values (>2000 tons/km²) concentrated in the southeastern permanent vegetation zones and lower values (<800 tons/km²) predominating in the southwestern desert margins. This spatial distribution correlates strongly with land use types and is influenced by both precipitation variability and soil conservation engineering measures like slope water storage and soil conservation engineering, gully and river valley regulation engineering, windbreak and sand fixation engineering, and water resource regulation and water-saving engineering. Notably, the peak conservation capacity in 2010 coincided with the maximum vegetation coverage, suggesting the existence of specific ecological threshold effects that influence the dynamics of soil conservation services.

The Hexi Corridor experienced a significant 129% increase in its vegetation carbon sequestration capacity, rising from 156 g C/m² in 2000 to 357 g C/m² by 2020. This substantial enhancement underscores the success of China’s ecological restoration efforts, notably the “Grain for Green” program (converts erosion-prone farmland to vegetation to curb erosion) and various desertification control initiatives. Spatial analysis reveals pronounced heterogeneity in carbon sequestration across the region. Southeastern oasis areas, characterized by intensive agricultural practices and managed ecosystems, emerged as hotspots, exhibiting sequestration rates exceeding 400 g C/m². Conversely, the northwestern desert regions, limited by sparse photosynthetic activity, were registered as carbon sequestration coldspots, with values below 100 g C/m². This spatial disparity aligns closely with variations in land use intensity and the density of irrigation infrastructure, accentuating the pivotal role of human intervention in amplifying carbon sinks in these arid settings.

Within the Hexi Corridor, the primary grain production zones are predominantly located in its southeastern sections, where fertile croplands overlap with other essential ecosystem services (Wuwei Oasis, Zhangye Oasis, Linze Oasis, and Gaotai Oasis). This agglomeration contrasts sharply with the northern and eastern areas, where limited arable land and adverse natural conditions restrict agricultural production, thereby delineating distinct low-yield zones (Figure 2). From 2000 to 2020, the Hexi Corridor witnessed a consistent rise in grain productivity, increasing by 57% from 52 to 82 t/km². This growth reflects noticeable advancements in agricultural capacity, likely due to improvements in irrigation efficiency and the adaptation of crop management techniques suitable for the arid environment.

3.2. Analysis of the Trade-Off and Collaborative Relationship Between Grain Production Services and Other Services

Correlation analyses were conducted to explore the interactions between the water yield, soil conservation, vegetation carbon sequestration, and grain production in the Hexi Corridor from 2000 to 2020. The findings are summarized in

Table 2. Correlation coefficients between grain production services and other services (water yield, soil conservation, and vegetation carbon sequestration) in the Hexi Corridor from 2000 to 2020 (“**” represents significance at the 0.01 level and “***” represents significance at the 0.001 level).

Year	WY–GP	SC–GP	CS–GP
2000	0.419 **	0.668 ***	0.579 ***
2005	0.460 ***	0.605 ***	0.781 **
2010	0.407 **	0.591 ***	0.742 **
2015	0.497 **	0.611 ***	0.780 ***
2020	0.455 **	0.611 ***	0.779 **

.

The correlation analysis from 2000 to 2020 indicates consistent synergistic relationships among grain production, water yields, soil retention, and vegetation carbon sequestration (Table 1). Notably, vegetation carbon sequestration displayed the strongest correlation with agricultural output, peaking at an r-value of 0.779 in 2020. Soil retention followed, achieving a maximum correlation of 0.668 in 2000. The water yield exhibited relatively weaker linkages, with correlations ranging from 0.407 to 0.497. This hierarchy highlights the region’s distinctive agricultural dynamics—extensive irrigation infrastructure significantly decouples crop production from natural water availability. Simultaneously, sustained vegetation restoration efforts have progressively fostered carbon–food synergies. The observed fluctuations in water–food correlations, such as 0.497 in 2015 compared to 0.407 in 2010, likely arise from alternating wet and dry cycles and evolving water management policies. Efficient irrigation (drip, sprinkler) cuts waste and boosts the grain water use efficiency; upgraded facilities secure the dry year supply; and unified basin allocation (e.g., Heihe River) balances irrigation/ecology via annual rainfall adjustments. Tiered agricultural water pricing shifts planting to drought-resistant crops. Drought warnings protect critical crop water needs; groundwater protection and ecological transfers (e.g., Qilian Mountain projects) stabilize farmland water. These dynamic policies interacting with wet–dry cycles drove correlation changes. Additionally, the increase in soil–food correlations post-2010, from 0.591 to 0.643, underscores the delayed benefits associated with the adoption of conservation tillage practices—a process in which water plays a pivotal mediating role. By regulating the soil structure (e.g., facilitating aggregate formation) and driving biological processes (e.g., microbial-mediated decomposition of organic matter), water gradually improves soil fertility and crop growth conditions. Such water-driven soil–biological synergies require time to accumulate, meaning that the reinforcing effect of conservation tillage on soil–grain correlations is characterized by a lag.

3.3. Temporal and Spatial Changes in Land Use Patterns

The land use and cover dynamics within the Hexi Corridor from 2000 to 2020 showcased considerable stability, sustaining a typical arid landscape configuration. Analysis indicates the prevailing dominance of desert and Gobi ecosystems, which collectively accounted for approximately 67.3 ± 1.2% of the total land area throughout the period. Grasslands emerged as the second most prevalent category, comprising 22.1 ± 0.8% of the area, while cultivated lands were relatively scarce, covering just 5.9 ± 0.3%. Other land cover types—including forests (2.1%), water (1.4%), and construction land (1.2%)—formed less than 5% of the regional territory, underscoring the prevailing environmental constraints characteristic of this arid zone.

The Hexi Corridor witnessed significant land use transformations between 2000 and 2020, marked by conflicting pressures of economic development and ecological conservation (

Table 3. Land transfer matrix of Hexi Corridor from 2000 to 2020 (unit: km²).

Land Type in 2000	2020						Total
	Farmland	Woodland	Grassland	Water	Construction Land	Unused Land
Farmland	10,745	6	2297	14	21	69	13,152
Woodland	9	6884	194	2	3	4	7096
Grassland	2205	306	43,668	84	186	5645	52,094
Water	6	3	19	1721	1	193	1943
Construction land	4	1	5	0	465	2	477
Unused land	1601	253	9632	540	197	159,625	171,848
Total	14,570	7453	55,815	2361	873	165,538	246,610

). Cultivated land expanded markedly by 1418 km² (10.8%), predominantly in the southeastern and central regions, where fertile soils and water resources are abundant. This expansion of agriculture coincided with notable urbanization, as construction land increased by 396 km² (83%), distributed through scattered yet intensive development patterns, with annual urban growth rates exceeding 4.1%. Forest cover increased modestly by 357 km² (5%), primarily in the southeastern highlands, where precipitation sustains woodland ecosystems. Grasslands experienced the most substantial absolute growth, expanding by 3721 km² (7.1%) across various elevations through both natural regeneration and managed restoration initiatives. Waters expanded by 418 km² (21.5%), largely in the southern mountainous areas, nourished by glacial melt and precipitation. These gains were offset by a reduction in unused land, which diminished by 6310 km² (3.7%), especially in the northeast, where conversion to agricultural and urban uses was most pronounced. The spatial patterns highlight underlying tensions in this arid landscape: urban expansion has encroached upon 12% of prime farmland in burgeoning county seats, while also competing for scarce water resources—the municipal water demand now grows at a rate 2.3 times that of agricultural needs. Nearly one-quarter of new construction has supplanted former grassland areas, posing threats to vital ecosystem services. These dynamics emphasize the critical balance required to sustain the grain production capacity alongside economic growth in this ecologically vulnerable region.

Figure 3 illustrates the dynamic nature of land conversion within the study area, highlighting significant shifts across various land types. The predominant transformations occur between arable land, forest, and grassland, alongside the reclamation of previously unused land. Notably, unused land experiences the highest frequency of conversion. Moreover, significant changes are observed in the conversion of grassland and arable land, with grassland being the second most commonly altered land type. This includes the degradation of some grassland into unused land, likely attributable to water scarcity issues. Additionally, there are notable conversions of land to arable and forest land. Arable land frequently transitions into grassland, while the expansion of waters primarily results from the development of unused areas. Forest land increases are partially due to grassland conversion and also due to afforestation efforts on unused land. Construction land predominantly originates from grassland and unused land conversions, driven by demographic growth and accelerated urbanization, necessitating urban development.

3.4. Hotspot Analysis of Grain Production Services

Utilizing the ArcGIS platform, a 6 km by 6 km grid serves as the unit of analysis for hotspot detection, ensuring sufficient data coverage within each grid and balancing computational efficiency with resource consumption. The analysis results, depicted in Figure 4, identify three levels of hotspot areas based on statistical significance: extremely significant hotspots (99% confidence), significant hotspots (95% confidence), and general hotspots (90% confidence). These are predominantly located in the southeastern part of the Hexi Corridor. The extremely significant hotspot areas are extensively distributed in the southeast, while the significant and general hotspots are more localized around these regions. Conversely, the coldspot areas, defined at a 90% confidence level, primarily occupy the western sector of the region. Over the period from 2000 to 2020, both hotspots and coldspots expanded in area. Examining the spatial distribution of grain production services, it is evident that the distribution of hot areas within the Hexi Corridor closely aligns with regions of high-value grain (corn and wheat) production services. Conversely, the distribution of cold and statistically insignificant areas corresponds broadly with regions characterized by low-value grain production services. In terms of land use, the hotspot areas coincide predominantly with cultivated land, while the coldspot and insignificant areas are primarily associated with non-cultivated land, such as sandy areas, Gobi desert, bare rocky terrain, grassland, and water. Among these, the coldspot areas predominantly consist of sandy lands that are unsuitable for plant growth.

Our investigation into the dynamics of ecosystem service interactions within designated hotspots has uncovered enhanced synergistic relationships, surpassing those observed in regional comparisons (

Table 4. Person correlation coefficients between grain production services and other services (water yield, soil conservation, and vegetation carbon sequestration) in the hotspot areas of grain production services in the Hexi Corridor from 2000 to 2020.

Year	WY–GP	SC–GP	CS–GP
2000	0.370 ***	0.701 ***	0.722 ***
2005	0.343 ***	0.693 **	0.837 **
2010	0.382 **	0.634 ***	0.861 **
2015	0.369 **	0.728 ***	0.823 ***
2020	0.327 **	0.736 ***	0.846 **

Note: “**” represents significance at the 0.01 level and “***” represents significance at the 0.001 level.

). Over the period from 2000 to 2020, the Hexi Corridor, noted for its grain production hotspots, demonstrated significantly stronger positive correlations among the water yield, soil retention, and vegetation carbon sequestration services compared to the broader study area. The hierarchical arrangement of interaction strengths aligned with regional trends, with vegetation carbon sequestration exhibiting the strongest linkage to agricultural productivity. This was followed by soil conservation and, subsequently, water provision. Although the correlations between water and grain production in hotspots were slightly weaker than the regional averages, the connections between the other service pairs showed pronounced enhancements within these intensively managed agricultural zones. Such spatial distinctions imply that human interventions, especially in the form of irrigation infrastructure (sprinkler irrigation and drip irrigation facilities) and conservation tillage, have intensified certain ecosystem service synergies, while simultaneously leading to minor decoupling between hydrological and agricultural systems in areas of high productivity.

Further geospatial analysis delineated the relative contributions of key ecosystem services to grain production patterns within these hotspot areas (

Table 5. Explanatory power of other services (water yield, soil conservation, and vegetation carbon sequestration) on the spatial distribution of grain production services in the hotspots in the Hexi Corridor from 2000 to 2020.

Year	WY–GP		SC–GP		CS–GP
	q	p	q	p	q	p
2000	0.31	0	0.52	0	0.44	0
2005	0.34	0	0.56	0	0.42	0
2010	0.28	0	0.51	0	0.48	0
2015	0.35	0	0.46	0	0.43	0
2020	0.31	0	0.57	0	0.41	0

). During the same two-decade period, soil conservation services displayed the highest explanatory power (mean r = 0.52), underscoring the critical agricultural dependency on soil quality, where factors such as fertility maintenance and erosion prevention are directly linked to crop productivity. Vegetation carbon sequestration held a secondary influence (mean r = 0.44), functioning through indirect mechanisms such as microclimate regulation and enhancements in ecological stability. Conversely, the water yield exhibited a comparatively limited explanatory role (mean r = 0.32), a typical characteristic of irrigated agricultural systems in arid settings, where the engineered water supply partially decouples production from natural water availability. This hierarchy of influences remained consistent over time, albeit with significant interannual variability related to climatic changes and management practices.

3.5. The Impact of Irrigation Factors on Grain Yields in Hot Areas of Grain Production Services

The dynamics of irrigation water usage in grain production hotspots were meticulously quantified through the analysis of official water resource bulletins issued by Gansu Province for the years 2000, 2005, 2010, 2015, and 2020. This analysis unveiled significant spatiotemporal patterns in agricultural water consumption and conservation practices (

Table 6. Grain yield, irrigation water consumption, and water-saving irrigation areas in the hotspots of grain production services in the Hexi Corridor region from 2000 to 2020.

Year	Grain Yield (t/km2)	Irrigation Water Consumption (Billion m3)	Water-Saving Irrigation Area (Ten Thousand Acres)
2000	171	42.47	564.57
2005	193	46.07	673.45
2010	217	45.29	699.53
2015	239	45.88	805.07
2020	246	40.12	987.80

). The dataset delineates the progression of water-saving irrigation infrastructure within the Hexi Corridor’s most productive agricultural zones, where intense cultivation occurs alongside critical water shortages.

The designated grain production hotspots in the Hexi Corridor exhibited a consistent increase in yield from 2000 to 2020, escalating from 171 to 246 t/km². Concurrently, these areas maintained remarkable stability in water usage. Despite intensified production, the total irrigation water consumption exhibited minor fluctuations within a narrow band of approximately 4.397 ± 0.23 billion m³ annually. This was facilitated by the significant expansion of water-saving irrigation systems, growing from 564,570 to 987,800 mu. Such decoupling of productivity gains from the water demand underscores substantial advancements in irrigation efficiency, which increased by 23.7%. This enhancement is attributable to three synergistic factors: (1) agricultural restructuring towards high-value crops, (2) optimized planting patterns, and (3) the adoption of advanced irrigation technologies. The stable water footprint amidst production growth underscores the success of water productivity interventions in this arid region.

Statistical relationships between agricultural productivity and water management indicators were rigorously quantified through Pearson correlation analysis of the grain yield, irrigation water usage, and water-saving irrigation area in the Hexi Corridor’s production hotspots for the period 2000–2020 (

Table 7. Table of person correlation coefficients for grain yield, irrigation water consumption, and water-saving irrigation area in the research area.

Factor	Grain Yield	Significance
Irrigation water consumption	−0.15	Not significant
Water-saving irrigation area	0.92 *	0.05 level

Note: “*” represents significance at the 0.1 level.

). The correlation matrix elucidates critical linkages between cropping intensification and the development of water conservation infrastructure in this water-scarce region.

The correlation analysis, as shown in Table 6 and Table 7, indicates no significant relationship between grain yields and total irrigation water consumption (p > 10). In contrast, a strong positive correlation exists with water-saving irrigation areas (r = 0.92, p < 0.05). This marked correlation underscores the essential role that efficient irrigation technologies play in enhancing agricultural water productivity within arid environments. By substantially improving the efficiency of water delivery and decreasing conveyance losses, water-saving irrigation systems significantly increase the proportion of water resources that are effectively utilized for crop growth, thereby fostering conditions conducive to yield enhancement. These findings support the assertion that the expansion and enhancement of water-saving irrigation infrastructure are viable strategies for achieving sustainable yield intensification in water-scarce agricultural settings.

4. Discussion

4.1. Balancing and Coordinating Between Grain Production and Other Services in the Hexi Corridor Region

This study utilizes an integrated multi-source remote sensing methodology alongside the InVEST and CASA models to quantify four essential ecosystem services within the Hexi Corridor: water yields, soil retention, vegetation carbon sequestration, and grain production. Our findings indicate significant spatial heterogeneity, with service hotspots predominantly located in the southern and southeastern sectors, whereas coldspots are prevalent in the eastern and northeastern regions [43]. The interplay of services reveals robust synergies among grain production, water provision, carbon sequestration, and soil conservation—a pattern consistent with previous studies in Northwest China [44]. Notably, this stands in contrast to the trade-offs observed between agricultural production and soil conservation in other arid regions [44,45], a difference that can be attributed to three localized factors: the adoption of innovative water-saving irrigation technologies, the strategic optimization of crop structures, and the implementation of precision conservation tillage. For example, the promotion of mulch drip irrigation in Ganzhou District in Zhangye and the adoption of “no-tillage + straw mulching” in Minqin County in Wuwei have both facilitated simultaneous improvements in yield and soil protection. Additionally, the dynamics of land conversion [46], particularly the transition from grassland to cropland as identified by Pan et al. [44], may influence service relationships, highlighting both the spatial complexity of ecosystem service interactions and the imperative for context-specific policy frameworks that balance ecological preservation with agricultural intensification in arid environments.

To bolster the synergistic interactions between ecosystem services and grain production in the Hexi Corridor, a three-pronged management strategy is recommended. Given the region’s arid climate and reliance on irrigated agriculture, a priority should be the modernization of irrigation infrastructure through the widespread implementation of precision technologies (e.g., drip and sprinkler irrigation systems) to reduce conveyance losses and optimize the water distribution between areas with surpluses and deficits [47]. In parallel, targeted revegetation initiatives should be launched in ecologically appropriate zones, utilizing drought-resistant species with high carbon sequestration capacities (e.g., Haloxylon ammodendron, Tamarix spp.) to enhance carbon storage and microclimate control while restoring degraded landscapes through the Grain-for-Green initiative (converting erosion-prone farmland to vegetation to curb erosion). Complementary to these efforts, comprehensive soil conservation practices incorporating terracing, check dams, and conservation tillage (no till or reduced tillage) should be implemented across arable land to simultaneously mitigate erosion, increase soil organic matter, and improve the water retention capabilities. This integrated management approach is poised to augment grain productivity while advancing water usage efficiency, thereby fostering a mutually beneficial cycle between ecological preservation and agricultural intensification in this delicate arid ecosystem.

4.2. The Impact of Irrigation Factors on Grain Production Services

The synergy between grain production and water yields in the Hexi Corridor is characterized by a notably weaker correlation coefficient compared to other service relationships, highlighting the unique agricultural hydrology of the region. As an archetypal snowmelt-fed oasis agricultural system, crop cultivation is fundamentally reliant on engineered water management derived from the glacial sources of the Qilian Mountains [48]. The three primary river systems—Shule, Shiyang, and Heihe—have been extensively regulated through networks of dams and canal infrastructure, which centralize both water resources and human settlements within these artificially maintained fertile zones [49]. Provincial water records indicate significant disassociation between stable irrigation water consumption and substantial increases in grain yield, primarily attributed to the expansion of water-saving irrigation in the region. This separation underscores that advancements in irrigation efficiency, rather than mere increases in water volume, have propelled agricultural intensification. Therefore, strategic investments in precision irrigation infrastructure and the adoption of water-saving techniques represent the most sustainable avenues for continuing productivity enhancements in this water-limited environment.

In the arid Hexi Corridor, optimizing the water–food nexus necessitates integrated adaptive management strategies. The modernization of irrigation should give precedence to high-efficiency systems, including field water conservation techniques, mulching practices, and drip fertigation, to supplant traditional flood irrigation methods. These modifications could potentially reduce agricultural water usage by 30–40% while sustaining yields [50]. Dynamic water allocation mechanisms must adapt to interannual hydrological variability by adjusting withdrawal quotas based on the real-time monitoring of precipitation, surface flow, and groundwater levels. Furthermore, optimizing the crop structure through scientific rotation cycles and strategic fallowing can enhance water productivity, especially by balancing water-intensive crops, such as corn, with drought-resistant alternatives. Simultaneously, accelerating the innovation of scalable water-saving technologies and developing crop varieties that require lower water inputs through targeted R&D investments will be crucial for sustainable intensification. These coordinated measures can significantly increase the water usage efficiency while ensuring food security in this fragile arid ecosystem [51,52].

4.3. Balance and Synergy Between Grain Production Services and Other Services in Hot Areas of Grain Production Services

The spatial heterogeneity of geographic environments leads to scale-dependent effects in ecosystem service interactions [53,54]. Throughout the period from 2000 to 2020, while consistent synergistic patterns were maintained, the grain production hotspots in the Hexi Corridor displayed varied correlation intensities: water production services demonstrated weaker coupling, whereas vegetation carbon sequestration and soil conservation exhibited stronger associations compared to regional averages. Such scale divergence highlights that relationships at regional levels cannot be indiscriminately applied to local or micro-scale contexts, thereby reflecting significant variations in anthropogenic pressures, land use configurations, and the distribution of natural capital across different spatial hierarchies. For instance, at the regional scale, anthropogenic pressures are more manifested as macro-policy orientations and structural interventions, such as policies promoting agricultural expansion across the entire Hexi Corridor, the Heihe River water allocation system, and projects like the Three-North Shelterbelt. These pressures shape the overall regional land use patterns (e.g., the distribution of oasis agricultural belts and desert transitional zones) and resource allocation models, with extensive and systemic impacts. At the local or micro scale, however, anthropogenic pressures exhibit high heterogeneity and localization. For example, in specific townships or farmers’ plots, such pressures may be reflected in small-scale differences in farming practices (e.g., adoption of no tillage or crop rotation), choices of irrigation technologies (e.g., traditional flood irrigation vs. drip irrigation), varying amounts of chemical fertilizers and pesticides applied, or even the intensity of individual farmers’ investments in land. These micro-level human activities directly affect local ecosystems, and their intensities and modes are often closely linked to the implementation details of regional macro-policies, local economic conditions, and farmers’ perceptions. Such differences may lead to the divergence of the same “regional-level relationship” at the micro scale. For example, while there is an overall trend of “agricultural production expansion accompanied by increased water resource pressure” at the regional scale, the opposite relationship—“yield improvement but reduced water resource pressure”—may emerge at the micro scale due to a village’s adoption of high-efficiency water-saving technologies. The mechanisms underlying these scale-dependent effects require further investigation to clarify how landscape organization influences service interactions in arid agroecosystems.

During the same period, strong synergies were observed among grain production, vegetation carbon sequestration, and soil conservation services in hotspot areas, with geospatial analysis pinpointing soil conservation as the primary explanatory factor. To boost agricultural productivity in these intensive cultivation zones, a prioritized management strategy is imperative. Firstly, grassland conservation should be strengthened due to its superior soil retention capabilities [45], which necessitates optimized grazing regimes, enhanced pasture management, and stringent restrictions on the conversion of grassland to built-up areas. Simultaneously, the protection of forest ecosystems must be intensified owing to their unmatched carbon sequestration capacities [45], requiring robust conservation efforts for public welfare forests, the preservation of natural forests, and prohibitions on commercial logging. Special attention is warranted for three vulnerable eastern sub-hotspots (Figure 4)—oasis agricultural zones with compromised ecosystem service levels. These areas require dual interventions: ecological restoration through desert greening initiatives to bolster soil and vegetation services and the optimization of agricultural water usage through improvements in irrigation efficiency, thereby ensuring sustainable intensification in these marginal production zones [55].

4.4. Limitations and Future Prospects

Grain production in the Hexi Corridor is subject to a complex array of determinants beyond the ecosystem services analyzed in this study. Key agricultural inputs such as fertilizer application rates, total agricultural machinery power, and rural electricity consumption exhibit significant positive correlations with yield outputs [56,57,58,59]. External socioeconomic factors, including government subsidy programs and grain pricing mechanisms [60], also exert substantial influences, where effectively designed policy incentives and market-based pricing signals can significantly enhance production intensification. Additional factors including pest management strategies, rates of technological adoption, and the frequency of natural disasters further contribute to this intricate interplay, although their specific impacts necessitate more systematic analysis in future research to delineate the optimal resource allocation frameworks for sustainable agricultural development in arid environments. In addition, this study did not analyze biological parameters such as metabolic coefficients, basal soil respiration, and some enzymatic activities. In the future, we will improve this aspect through field surveys and quantitative experiments, specifically by exploring the intrinsic mechanisms of regional patterns through micro-level biological processes.

5. Conclusions and Recommendations

This study utilizes integrated modeling approaches, specifically the InVEST and CASA models, to quantify and analyze the dynamics of grain production along with associated ecosystem services such as the water yield, soil conservation, vegetation carbon sequestration, and agricultural production in the Hexi Corridor. By conducting a comprehensive assessment of service interactions and focusing on agricultural hotspot regions, this research has elucidated several crucial findings. Firstly, from 2000 to 2020, the Hexi Corridor experienced a marked increase in agricultural intensification, with grain yields progressively rising from 52 to 82 tons per square kilometer. This growth in production was accompanied by an enhancement in its ecosystem service capacity, evidenced by positive temporal trends in the water yield, soil retention, and vegetation carbon sequestration. Notably, vegetation carbon sequestration exhibited the strongest correlation with agricultural productivity, followed by soil conservation and water provision. This indicates a hierarchical synergy structure where biophysical processes that most directly support plant growth are closely linked to crop yields. Secondly, given its arid climate and reliance on alpine snowmelt for irrigation, the Hexi Corridor’s agricultural system is distinctly different from traditional mainland farming practices. The analysis indicates that the adoption of water-saving irrigation technologies, such as drip and sprinkler systems, and expanding their implementation are the most effective strategies for sustainable yield intensification in this water-limited environment. These technologies have the potential to achieve 18–22% increases in productivity while simultaneously reducing agricultural water withdrawals by 30–35%. Thirdly, during the period from 2000 to 2020, grain production hotspots within the Hexi Corridor demonstrated significantly stronger synergistic relationships with the water yield, soil conservation, and vegetation carbon sequestration services compared to regional averages. Soil conservation emerged as the dominant explanatory factor for these relationships, followed by carbon sequestration and water provision, indicating that soil-related factors exert the primary influence over agricultural productivity in these zones of intensive cultivation.