Spatial-Temporal Assessment of Water Resource Security Based on Agricultural Water Footprint: A Case Study of Hotan Prefecture, Xinjiang

ZHANG Lili¹,², DENG Xiaoya², LONG Aihua¹,², GAO Haifeng³, REN Cai¹,², LI Zhiyun¹,²

¹College of Water & Architectural Engineering, Shihezi University, Shihezi, Xinjiang 832000, China
²State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
³Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment, Beijing 100094, China

Abstract

Hotan Prefecture represents a typical inland arid region where investigating regional water resource security holds significant importance for guiding water resource development and utilization while promoting sustainable socioeconomic and water resource development. Based on water footprint theory, this study examines the composition and spatiotemporal dynamics of agricultural production water footprints in Hotan from 1989 to 2018, encompassing both crop production and animal product production. Water resource security status is then analyzed and evaluated through water footprint intensity and water resource pressure indicators from the perspectives of water consumption and pollution. The results demonstrate that agricultural production water footprints in Hotan experienced three distinct phases: rapid growth, slow growth, and significant decline, composed at an approximate 8:2 ratio between crop production and animal product production water footprints. Stage-specific variations were dominated by fluctuations in the blue water footprint of crop production, exhibiting a spatial pattern of high values in the west and low values in the east. Water footprint intensity decreased logarithmically, shrinking to 1/19 of its original value by 2018, while water resource pressure values remained below 1 for many years, indicating a secure water resource status, though pressure has been relatively high in the past decade. Overall, agricultural production water footprints in Hotan have shown fluctuating growth over time, water use efficiency has improved significantly, yet water resource pressure has increased simultaneously, continuously threatening regional water resource security.

Keywords: crop production water footprint; animal product production water footprint; grey water footprint; water resource security; Hotan Prefecture

1. Study Area and Methods

1.1 Study Area Overview

Hotan Prefecture is located in the hinterland of the Eurasian continent at the southernmost tip of Xinjiang Uygur Autonomous Region (77°20′~85°E, 34°~39°30′N), covering a total area of 24.78×10⁴ km² and jurisdiction over 24 counties and townships (Fig. 1). The region represents a typical inland arid zone characterized by scarce annual precipitation, abundant sunlight, rich heat resources, long frost-free periods, and large diurnal temperature variations. With average annual precipitation of 35 mm, surface runoff replenishment primarily depends on melted glaciers and snowpack plus some alpine precipitation, resulting in substantial interannual variability in river runoff fluctuating by 20%~40% annually. The area contains 74 rivers of varying sizes with total annual runoff of 73.4×10⁸ m³, among which the Yulong Kashi River and Kara Kashi River account for 85.94% of the region's total water volume. These two rivers converge near Koshlash to form the Hotan River, which serves as a crucial ecological corridor preventing the eastern and western halves of the Taklimakan Desert from merging.

According to the Xinjiang Water Resources Bulletin, Hotan Prefecture's average annual agricultural water consumption exceeds 95% of total water use, comprising crop irrigation water and animal husbandry water at approximately a 6:1 ratio. The Hotan Statistical Yearbook indicates the prefecture currently has 133 irrigated areas above designated size, predominantly small-scale irrigation districts, with two districts exceeding 3.33×10³ hm². Major crops include wheat, coarse grains, and cotton.

1.2 Data Sources

Data required for calculating agricultural production water footprints were obtained from the Xinjiang Statistical Yearbook (1990–2019) and Xinjiang Production and Construction Corps Statistical Yearbook (1990–2019) for crop planting area, fertilizer use, animal headcounts, and water footprint efficiency indicators. Available water resources data for water resource pressure calculations were sourced from the Xinjiang Water Resources Bulletin (2004–2019). Meteorological data needed for calculating crop evapotranspiration—including annual rainfall, average wind speed, relative humidity, maximum temperature, and minimum temperature from Hotan meteorological stations—were obtained from the National Meteorological Science Data Sharing Service Center (http://data.cma.cn). To assess overall regional water resource security, this study includes the 14th Division of the Xinjiang Production and Construction Corps within the research scope, incorporating various regiments into their respective jurisdictions for calculation and analysis of agricultural production water footprints without separate analysis.

1.3 Calculation Methods

1.3.1 Agricultural Production Water Footprint Calculation

Based on water footprint theory, this study calculates blue, green, and grey water footprints for agricultural production in Hotan from the producer perspective. Considering pollutant emissions, environmental sensitivity, and data availability, the primary pollutants selected for grey water footprint analysis were ionic chemical oxygen demand (COD), total nitrogen (TN), and ammonia nitrogen (NH₃-N). Agricultural production water footprints are represented by crop production and animal water footprints using the formula:

$$WF_{agr} = WF_{cul} + WF_{ani}$$

where $WF_{agr}$ is agricultural production water footprint; $WF_{cul}$ is crop production water footprint; and $WF_{ani}$ is animal product production water footprint.

1.3.2 Crop Production Water Footprint

Crop production water footprint refers to water resources consumed during crop growth, which can be further divided into blue, green, and grey water footprints based on water resource type and environmental impact. The calculation method is:

$$WF_{cul} = WF_{blue} + WF_{green} + WF_{grey}$$

where $WF_{cul}$ is crop production water footprint (m³·yr⁻¹); $WF_{blue}$, $WF_{green}$, and $WF_{grey}$ are blue, green, and grey water footprints of crop production, respectively (m³·yr⁻¹).

Blue and green water footprints are calculated as:

$$WF_{blue} = \frac{CWU_{blue}}{Y} = \frac{10 \times \sum d_{blue}}{Y}$$

$$WF_{green} = \frac{CWU_{green}}{Y} = \frac{10 \times \sum d_{green}}{Y}$$

where $CWU_{blue}$ and $CWU_{green}$ are crop blue and green water requirements (m³·hm⁻²); $Y$ is crop yield per unit area (kg·hm⁻²); $d_{blue}$ and $d_{green}$ are daily crop blue and green water use (mm); the coefficient 10 is a constant factor; and the summation represents accumulation from planting date to harvest date.

The green water footprint is calculated as $d_{green} = \min(ET_c, P_e)$, and the blue water footprint as $d_{blue} = \max(0, ET_c - P_e)$, where $ET_c$ is crop evapotranspiration (mm·d⁻¹) and $P_e$ is effective rainfall (mm). $ET_c$ is calculated using the FAO-56 standard crop coefficient and correction formula, adjusted according to study area climate, soil, crop, and irrigation conditions. $ET_0$ is reference crop evapotranspiration (mm·d⁻¹) calculated using the Penman-Monteith formula.

The grey water footprint of crop production primarily refers to water resources required to dilute pollution ions from unused fertilizers leached into rivers by irrigation or rainfall to standard concentrations. This study analyzes nitrogen and phosphorus fertilizers—the most widely applied in Hotan—as primary pollution sources. Since the same water body can dilute multiple pollutants simultaneously, the grey water footprint is determined by the maximum water requirement among pollutant ions. The calculation formula is:

$$WF_{grey} = \max(WF_{grey,N}, WF_{grey,P})$$

$$WF_{grey,N} = \frac{L_N \times A}{C_{max,N} - C_{nat,N}}$$

$$WF_{grey,P} = \frac{L_P \times A}{C_{max,P} - C_{nat,P}}$$

where $\alpha_N$ and $\alpha_P$ are fertilizer leaching coefficients for nitrogen and phosphorus fertilizers, respectively, taken from the First National Pollution Source Census Coefficient Manual; $A$ is fertilizer application amount (kg); $C_{max,N}$ and $C_{max,P}$ are maximum pollutant concentrations under environmental water quality standards, with $C_{max,N} = 0.01$ kg·m⁻³ and $C_{max,P} = 0.005$ kg·m⁻³ from the Integrated Wastewater Discharge Standard (GB8978-2002); and $C_{nat,N}$ and $C_{nat,P}$ are natural background concentrations of receiving water bodies, assumed to be 0.

This study focuses on major crops in Hotan, including grain crops (rice, wheat, coarse grains, beans), economic crops (cotton, oil crops, sugar beets, vegetables, melons, potatoes, alfalfa), and fruits (grapes, apples, pears, dates, other fruits), analyzing water footprint variation patterns across counties and crops from 1989 to 2018.

1.3.3 Animal Product Production Water Footprint

Animal product production water footprint refers to the water footprint throughout an animal's entire lifecycle from birth to slaughter, including virtual and direct water consumption for growth, feed processing, drinking water, cleaning service water, and grey water footprint primarily from animal excreta. The calculation formula is:

$$WF_{ani} = WF_{feed} + WF_{drink} + WF_{serve} + WF_{grey}$$

where $WF_{feed}$, $WF_{drink}$, $WF_{serve}$, and $WF_{grey}$ represent feed water, drinking water, service water, and grey water footprints, respectively (m³·yr⁻¹).

The feed water footprint is calculated as:

$$WF_{feed} = \sum_i SWC_i \times C_{mix,i} + \sum_i \int_{birth}^{death} C_{ij} dt$$

where $C_{mix,i}$ is water required for mixed feed (m³·yr⁻¹); $C_{ij}$ is the weight of feed $j$ consumed by animal $i$ (kg·d⁻¹); and $SWC_i$ is the virtual water content of feed $i$ (m³·kg⁻¹). Virtual water content of feed crops is calculated using the crop production water footprint method, weighted according to different feed crop ratios (by weight).

Drinking and service water footprints are calculated as:

$$WF_{drink} = \int_{birth}^{death} Q_i^d dt$$

$$WF_{serve} = \int_{birth}^{death} Q_i^s dt$$

The grey water footprint is calculated as:

$$WF_{grey} = \max_k \left( \frac{P_k \times \beta_k}{C_{max,k} - C_{nat,k}} \right)$$

where $P_k$ is the annual amount of pollutant $k$ generated in animal urine and feces (kg·yr⁻¹); $\beta_k$ is the loss rate of pollutant $k$ from animal excreta into water bodies, taken from the National Large-scale Livestock and Poultry Breeding Industry Pollution Survey Technical Report; $C_{max,k}$ is the environmental water quality standard value for pollutant $k$, with $C_{max,COD} = 0.06$ kg·m⁻³ and $C_{max,NH_3-N} = 0.015$ kg·m⁻³ from GB8978-2002; and $C_{nat,k}$ is the natural background concentration of the receiving water body.

This study uses live animal data, excluding feed crop production water footprints that overlap with crop production water footprints in growth and feed processing water use, to calculate animal water footprints for five major livestock types (cattle, horses, pigs, donkeys, sheep) in Hotan from 1989 to 2018.

1.4 Water Resource Security Evaluation Indicators

This study employs water footprint intensity and water resource pressure indicators to analyze and evaluate water resource security status in Hotan (Table 1). The Water Footprint Assessment Manual defines a product's water footprint as the sum of water used throughout its entire production supply chain—a multi-dimensional indicator reflecting water consumption volume, water source type, pollution amount, and pollution type. Blue and green water footprints primarily reflect consumed water volume and source type, while grey water footprints reflect pollution amount and type. To facilitate evaluation indicator calculation and result analysis, this study categorizes water footprints consumed in virtual and direct water forms as non-grey water footprints of agricultural production ($WF_{con}$), and the remainder as grey water footprints of agricultural production ($WF_{grey}$). Thus, $WF_{agr}$ can be expressed as:

$$WF_{agr} = WF_{con} + WF_{grey}$$

where $WF_{con}$ is agricultural production non-grey water footprint (m³·yr⁻¹) and $WF_{grey}$ is agricultural production grey water footprint (m³·yr⁻¹).

Water resource security evaluation indicators include water footprint intensity and water resource pressure indicators. Water footprint intensity reflects water resource utilization efficiency, expressed as agricultural production water footprint per unit of GDP. Smaller values indicate higher water resource utilization efficiency. The calculation formula is:

$$WFS = \frac{WF_{agr}}{GDP}$$

Water resource pressure indicators reflect water resource pressure status and utilization security degree, expressed as the ratio of agricultural production water footprint to available water resources ($Q$). The calculation formula is:

$$WFP = \frac{WF_{agr}}{Q}$$

When $WFP < 1$, available water resources can meet consumption demand and regional water resources are secure; when $WFP = 1$, water resources are at critical security with available resources equal to consumption demand; when $WFP > 1$, consumption exceeds available resources and water resource utilization is insecure.

To better evaluate water resource pressure status in Hotan, this study classifies water resource pressure indicators into levels following reference [24] (Table 2).

2. Results

2.1 Composition and Spatiotemporal Changes of Agricultural Production Water Footprint

2.1.1 Crop Production Non-Grey Water Footprint

The crop production non-grey water footprint ($WF_{con,cul}$) comprises the sum of crop production green water footprint ($WF_{green,cul}$) and blue water footprint ($WF_{blue,cul}$), reflecting water resource consumption during crop production. Across Hotan from 1989 to 2018, $WF_{con,cul}$ for different crop types (grain crops, economic crops, fruits) showed fluctuating growth trends, dominated by grain crop consumption followed by economic crop consumption. Except for Minfeng County, all counties and cities exhibited $WF_{con,cul}$ growth, with wheat, coarse grains, cotton, and alfalfa—the four most extensively planted crops—accounting for 59%~96% of county-level $WF_{con,cul}$. Due to policy-guided planting area fluctuations, $WF_{con,cul}$ for wheat and coarse grains showed irregular large-amplitude changes. As a characteristic economic crop in Hotan, $WF_{con,cul}$ for red dates increased rapidly, closely related to the promotion of red date industry and policy encouragement for planting [29]. In regional red date cultivation, Hotan City showed no significant growth, while Minfeng County exhibited the most remarkable increase. From 2009, Minfeng County's economic crops, dominated by red date water consumption, exceeded grain crops and fruits in production water consumption, reaching 46.3% of crop production non-grey water footprint by 2018, becoming an important crop for local farmers' income and county-wide per capita income improvement.

Significant spatial differences in $WF_{con,cul}$ resulted from combined effects of water resource spatial distribution and inter-regional crop development. Among Hotan counties, Moyu, Hotan, and Luopu counties—located along the Hotan River with large populations, extensive crop planting areas, high agricultural output values, and relatively developed agricultural economies—showed significantly higher $WF_{con,cul}$ than other counties and cities, supported by water resources from the Hotan River despite large water consumption demands from extensive crop cultivation.

2.1.2 Animal Product Production Non-Grey Water Footprint

Animal product production non-grey water footprint ($WF_{con,ani}$) includes water for growth, feed processing, drinking, and cleaning services, reflecting water resources consumed from birth to slaughter. Hotan $WF_{con,ani}$ showed unsteady growth over time, increasing by 381.78% from 1989 to 1999, then decreasing by 32.8% from 1999 to 2009, followed by another increase. The number of animals directly impacted $WF_{con,ani}$ changes. With relatively stable feed structure and service/drinking water consumption, large livestock numbers decreased from 9.71×10⁶ heads in 1999 to 7.58×10⁶ heads in 2009, causing $WF_{con,ani}$ reduction. County-level contributions to Hotan's animal water consumption were largest from Moyu County and smallest from Minfeng County. Moyu County's $WF_{con,ani}$ reached its historical maximum of 1.09×10⁸ m³ in 1999, accounting for 29.3% of Hotan's $WF_{con,ani}$ that year. As the main contributor to animal water consumption in Hotan, Moyu County's changes significantly influenced regional $WF_{con,ani}$ dynamics.

2.2 Analysis of Agricultural Production Water Footprint Change Process

From 1989 to 2018, Hotan's agricultural production water footprint ($WF_{agr}$) experienced three stages: rapid growth (1989–1999), slow growth (1999–2009), and obvious decline (2009–2018). Stage-specific $WF_{agr}$ changes were dominated by crop production blue water footprint ($WF_{blue,cul}$) fluctuations, corresponding to $WF_{blue,cul}$ increase, basic stability, and decrease in the three stages, respectively.

Continuously expanding crop planting areas increased water consumption for crop growth. Under Hotan's arid climate, this intensified demand for blue water resources, creating the rapid growth stage of agricultural production water footprint. During 1989–1999, $WF_{agr}$ increased from 5.94×10⁸ m³ to 17.45×10⁸ m³, with an average annual growth rate of 10.36%. The slow growth stage (1999–2009) featured relative stability of $WF_{blue,cul}$. $WF_{agr}$ increased from 17.45×10⁸ m³ to 19.36×10⁸ m³, with $WF_{blue,cul}$ increasing by only 182.13% and $WF_{ani}$ increasing by 91.83%. The obvious decline stage (2009–2018) showed clear decreasing trends, with $WF_{agr}$ decreasing from its peak of 19.36×10⁸ m³ to 14.17×10⁸ m³, and $WF_{blue,cul}$ decreasing from its peak of 7.69×10⁸ m³ to 5.68×10⁸ m³, representing reductions of 26.93% and 32.12%, respectively.

Spatially, $WF_{agr}$ showed an overall pattern of high values in the west and low values in the east, with Moyu County as the highest value in the west and Hotan City as a low-value enclave. In the east, Yutian County served as a high-value area separating Cele and Minfeng counties. The western region, as the origin and flow path of the Hotan River, has abundant water resources that greatly satisfy water demands along the route, creating high-value areas. The eastern region shows low values, with Cele and Minfeng counties maintaining relatively low water consumption levels for planting and animal husbandry.

In composition, agricultural production non-grey water footprint ($WF_{con}$) dominated $WF_{agr}$, accounting for over 97.61%. The proportion of $WF_{con}$ in $WF_{agr}$ first decreased then increased, reaching its highest proportion of 99.39% in 2018. Crop production and animal product production water footprints composed Hotan's $WF_{agr}$ at a ratio of 88.16%~95.71%. The increase in $WF_{grey}$ proportion in 1999 resulted from substantial increases in nitrogen fertilizer use during crop production, making agricultural production grey water footprint ($WF_{grey}$) rise to 2.38% of $WF_{agr}$. Chemical oxygen demand (COD) was the main pollution source in $WF_{grey}$, accounting for 50.82% of $WF_{grey}$ in various years, but its small proportion indicated no significant impact on Hotan's water resource security.

2.3 Water Resource Security Assessment Based on Agricultural Production Water Footprint

Based on agricultural production water footprint calculations, water resource security status was analyzed using water footprint intensity (WFS) and water resource pressure (WFP) indicators. As shown in Fig. 6, WFS showed a near-logarithmic decreasing trend, with 2009 as a sudden increase point. Water footprint consumption intensity (WFS_con) dominated WFS changes, showing a consistent logarithmic decrease, while grey water footprint intensity (WFS_grey) played a secondary role, also decreasing logarithmically. WFS decreased from 1.86 m³·yuan⁻¹ to 0.10 m³·yuan⁻¹, indicating that water resources consumed per unit GDP decreased by 94.44%, demonstrating significant improvement in water use efficiency. However, compared to economically developed regions, Hotan's water resource utilization efficiency remains relatively low. Compared with Beijing's WFS of 0.0028 m³·yuan⁻¹ in 2015 and Shaanxi Province's WFS of 0.0224 m³·yuan⁻¹, Hotan's WFS was 35.7 times and 4.5 times higher, respectively, indicating substantial potential for improvement.

Hotan's water resource pressure (WFP) showed fluctuating upward trends over time, with a slow decreasing trend after 2009, but values remained below 1, indicating persistent water resource security. According to water resource pressure level classification, WFP can be divided into two stages: 1989–2009 with medium-low water resource pressure, and 2009–2018 with basically high and very high pressure states. This aligns with Wu Xuemei et al.'s [31] research results on water resource pressure status in Hotan from 2000 to 2013 through indicator system evaluation, reflecting secure water resource status.

Spatial distribution analysis (Fig. 7) revealed that in 1999, WFS showed a pattern of "one high, one low," with Hotan City as the lowest (0.03 m³·yuan⁻¹) and Minfeng County as the highest (10.93 m³·yuan⁻¹), while other counties ranged between 1.17–4.90 m³·yuan⁻¹. Compared with 1999, Hotan's water resource utilization efficiency improved significantly by 2018, with Minfeng County showing the most remarkable reduction of 10.63 m³·yuan⁻¹. Spatially, the contiguous area along the Hotan River (Hotan City, Moyu County, Hotan County, Luopu County, and Cele County) demonstrated higher water resource utilization efficiency than other counties.

Spatial patterns of WFP showed that in 1999, the county with highest pressure was Moyu County (WFP = 0.86), representing medium-high water resource pressure status, while Minfeng County had the lowest pressure (WFP = 0.25) with very low pressure status. By 2018, water resource pressure across Hotan counties generally increased, with only Minfeng County at medium status. Moyu, Hotan City, Hotan County, and Cele counties showed WFP values between 0.86–0.90, indicating very high water resource pressure status.

These results indicate that while counties like Moyu, Hotan City, and Cele showed smaller water footprint intensity values and higher water resource utilization efficiency, they were also high water resource pressure areas. Higher water resource utilization efficiency generates greater economic benefits but also demands more water resources, demonstrating the inevitable link between economic development and water resource demand. Better economic development requires certain water resource support.

3. Conclusion

Based on agricultural production water footprints in Hotan from 1989 to 2018, this study analyzed and evaluated regional water resource security status, yielding the following main conclusions:

1) Agricultural production non-grey water footprint accounted for over 97.61% of regional agricultural production water footprint. County-level crop production non-grey water footprint ($WF_{con,cul}$) showed fluctuating growth trends, dominated by grain crop consumption followed by economic crop consumption. Spatially, Moyu County showed the largest water resource consumption with an annual average $WF_{con,cul}$ of 3.80×10⁸ m³, while Minfeng County showed the smallest at 0.76×10⁸ m³.

2) Hotan's agricultural production water footprint ($WF_{agr}$) experienced three stages: rapid growth, slow growth, and obvious decline, primarily influenced by crop production blue water footprint fluctuations, peaking at 19.36×10⁸ m³ in 2009. Spatially, $WF_{agr}$ showed a west-high, east-low distribution pattern, with Moyu County as the highest value in the west and Yutian County as a high-value area separating Cele and Minfeng counties in the east.

3) Hotan's water resource status was secure from 1989 to 2018. Over time, regional water footprint intensity (WFP) decreased logarithmically, while water resource pressure (WFS) showed unsteady slow increase, indicating significant improvement in water resource utilization efficiency alongside increasing threats from water resource shortages.

Under policy support for "Comprehensive Paired Assistance to Xinjiang" and economic development opportunities from the "Belt and Road" strategy, Hotan will inevitably face further development challenges regarding whether regional water resources can meet economic development demands and how to resolve development-water demand conflicts. Future efforts should fully exploit water resource development potential, promote economic development in counties with lower water resource pressure and lagging development like Minfeng and Pishan, and seek balanced socioeconomic development across Hotan. Simultaneously, Hotan should actively respond to regional policies of farmland reduction and water-saving irrigation, reduce agricultural water use, strictly implement the "Three Red Lines" of water resource development and utilization, appropriately promote industrial development, and encourage low water-consuming, low energy-consuming agricultural product processing industries to improve economic benefits from agricultural production and further enhance water resource utilization efficiency and socioeconomic benefits, achieving synchronized improvement in water resource utilization efficiency and economic benefits.

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