Aeolian Environment Regionalization in Xinjiang and Suggestions for Sand Prevention in Typical Areas

Abstract

The Xinjiang region is prone to frequent and complex wind and sand disasters, which present a significant challenge to the sustainable development of local areas. This research uses multi-source data to analyze the spatial distribution of the aeolian environment in Xinjiang, establishes a four-level zoning scheme, and proposes recommendations for ecological management and engineering and control. Results indicate that (1) Xinjiang’s aeolian environment and its types exhibit spatial heterogeneity. The aeolian environment types display a high concentration in the eastern region and a low concentration in the western region. Furthermore, the aeolian environment types are concentrated in the basin region. Moreover, the aeolian environment types exhibit a meridional distribution pattern. (2) A four-level zoning system for aeolian environments in Xinjiang was developed, comprising two first-level zones, seven s-level subzones, 22 third-level wind zones, and 31 fourth-level subdivisions. (3) A structural model for a highway sand control system is proposed for aeolian environment types of subdivisions, including fixing-based, combined blocking and fixing, wind-blocking and sand-transferring, and combined blocking and fixing–transferring. The aeolian environment regionalization program proposed in this study can be a scientific reference for relevant departments in formulating and implementing sand prevention and control planning.

1. Introduction

Wind–sand activity is a complex surface process involving wind erosion, transport, and accretion, which can change the surface morphology and form unique wind–sand landscapes, and may cause wind–sand disasters [1]. Asia’s arid and semi-arid regions represent one of the largest dust sources in the world, with an estimated annual output of approximately 600 Mt of dust particles transported into the atmosphere [2]. This has been linked to many significant impacts on human health [3], marine biogeochemical cycles [4], nutrient supply to terrestrial ecosystems [5], and global climate change [6]. A wind–sand disaster is a natural phenomenon that can significantly impact the environment and human habitation. These disasters are characterized by a wide-ranging impact, strong seasonality, and a high degree of harm [7,8,9]. Xinjiang has long been subject to the destructive forces of wind and sand activities, which have posed a significant challenge to the safe operation of vital infrastructure in the region. The necessity for effective measures to mitigate the adverse effects of wind and sand disasters has become increasingly urgent [10].

The aeolian environment refers to natural environmental elements, such as climate and meteorology, geomorphology, and vegetation, among other elements, related to wind–sand activities and their combinations. The study of the aeolian environment has evolved from qualitative textual records to quantitative instrumental monitoring to comprehensive multi-source data analysis. This evolution has been accompanied by an expansion and deepening of the research content regarding spatial scales and time series.

Synthesizing domestic and international literature findings, research on aeolian environments can be divided into three categories: wind energy environments, sand and dust environments, and research that integrates both. The wind energy environment is typically investigated using only wind speed or measured data. Indicators such as wind speed [11], wind direction [12], and sand transport potential (RDP) [13] have been employed to characterize wind and sand activities, which are defined by a single source of data, a shorter time series, and a discontinuous record. Using these indicators to characterize the intensity of wind and sand activities at a single point is more appropriate. Using various data sources for sand and dust environmental research can provide insight into the range and intensity of actual sand and dust activities. Among the metrics commonly employed to indicate the intensity of modern wind and sand activities are the number of dust storm days [14], PM10 [15], aerosol optical thickness [16], and the extinction coefficient [17]. A series of dust indices based on spectral absorption differences have been generated, including the thermal infrared composite dust index [18] and the normalized difference dust index [19]. Yang et al. [20] analyzed the spatial and temporal changes in the risk of wind and sand disasters in the Sahel region from 2000 to 2020 and their main driving factors by comparing the applicability of different assessment methods and determining the optimal model. The analysis of wind and sand hazards was not conducted using multiple assessment methods in order to address the limitations of data availability and the complexity of the factors influencing these hazards. Wang et al. [21] assessed the risk of wind and sand disasters in Xinjiang from three aspects, based on the three-factor disaster theory: disaster-causing factors, the disaster-conceiving environment, and the disaster-bearing body, using subjective and objective methods.

For comprehensive research on aeolian environments, a multidisciplinary approach integrating climate, soil, topographic, and vegetation data can be employed. This approach enables the investigation of the complex interactions between wind and sand and their environmental effects. The resulting indices, such as wind erosion indices [22], climate erosivity indices [23], and dune movement indices [24], facilitate a quantitative understanding of these interactions. In addition, the regional aeolian environment types are typically described qualitatively based on expert knowledge, such as solid winds with more sand, weak winds with less sand, and so on. Although regional aeolian environmental conditions can be indicated to a certain extent, it is impossible to compare the differences between aeolian environment types in different regions due to the lack of a unified judgment standard. Furthermore, no quantitative research on aeolian environment types has been reported. Although there are no relevant research results on aeolian environment regionalization in China, much work has been done on zoning studies. These include “Evaluation of Desertification Disaster Hazard Zoning in Northern China” [24], “Ecological Zoning of Arid Regions in Northwestern China” [25], “Desertification Land Prevention and Control Zoning in Northern China (Outline)” [26], “Study of Desert and Desertification Land Zoning in Northern China Based on Remote Sensing Technology” [27], and “Study of Highway Desert Natural Zoning in China” [28]. Additionally, numerous studies focused on preventing and controlling desertification and the zoning of arid regions in China have been conducted; these include “Desertification Prevention and Control Zoning and Sub-zoning in Xinjiang Prevention and Control Technologies and Models” [29], “Zoning for Oasis and Desertification Regulation in Arid Regions of China” [30], and other zoning research results. These studies have integrated various factors, including geomorphology, climatic elements, geologic conditions, and desertification assessment results, to construct an evaluation index system and formulate zoning schemes with specific focuses. The existing studies have provided an essential reference for developing our study’s aeolian environmental zoning scheme.

Meteorological data are still predominantly employed to assess the intensity of wind and sand activities, and the resulting data can be utilized as a reference point. However, due to the significant regional variability in aeolian conditions, the results from individual stations can only partially capture the overall characteristics of the region. Consequently, there is a lack of long-term time series and high spatial accuracy in aeolian environment assessments based on remote sensing and re-analysis data. Second, the results of existing zoning research emphasize desertification and aeolian hazards, considering existing disaster-bearing factors. This quantification of the actual extent of the disaster can guide sand control and prevention work in Xinjiang to a certain extent. However, the data utilized in the existing studies are highly current, which results in a theoretically shorter update cycle for the zoning program and a shorter service timeliness. Given the research background and shortcomings mentioned above, in this paper, we have selected seven indicators: aeolian environment, RDP (Resultant Drift Potential), soil condition, vegetation cover, precipitation, and potential evapotranspiration to assess large-scale aeolian environmental results and proposed an aeolian environmental zoning scheme. Additionally, we suggest targeted countermeasures to be implemented for sand control and prevention work in typical areas. The object of this study is (1) to clarify the spatial distribution characteristics of the aeolian environment in the whole region of Xinjiang; (2) to formulate a zoning program for the aeolian environment in Xinjiang; (3) to put forward targeted ecological management measures and engineering configuration models. This research provides a scientific basis for realizing sustainable and economic protection projects.

2. Materials and Methods

2.1. Study Area

The study area is the Xinjiang Uygur Autonomous Region (Figure 1), which encompasses 1,664,900 km² and is situated in the hinterland of the Asian and European continents. Its coordinates are 73°30′–96°23′ E and 34°20′–49°10′ N. Xinjiang’s geographic location and geomorphological pattern have resulted in the formation of a typical temperate continental arid climate. This climate is characterized by scarce rainfall and strong evaporation, with an average annual precipitation of 141.8 mm across the entire region. Additionally, there is a vertical differentiation of soil moisture with elevation changes and significant differences in the landscape types and patterns between the mountainous areas and basins [31]. The topography of Xinjiang is characterized by a landscape of basins and mountains, collectively referred to as the “three mountains and two basins”. The Altai Mountains are located in the northern region, while the Kunlun Mountain system is situated to the south. The Tianshan Mountains span across the central area of Xinjiang. Xinjiang is geographically divided into two distinct regions: the Tarim basin in the south and the Junggar basin in the north.

The arid zone of Xinjiang encompasses an area of 1.227 million km² and has developed several significant wind-formed landforms. The Gurbantunggut desert, the Taklamakan desert, the Kumtag desert, and the Hashun Gobi are regions with strong winds and abundant sources of sand, which provide the dynamic conditions and material basis for wind and sand activities. The coupling effect of the nature of the subsurface and atmospheric circulation in the region is extremely complex, resulting in significant spatial differences in the aeolian environment [32]. Consequently, the wind and sand control measures need to be adjusted accordingly. For example, it has been recommended that, in the area of quicksand gathering, more grass squares and high vertical sand barriers can be used to impede the forward movement of the sand source [33], and the Gobi region can be set up to avoid the accumulation of the sand source in the downwind project [34]. The frequent occurrence of sandstorms in Xinjiang has posed a significant threat to the safe operation of engineering facilities; for instance, the sand burial phenomenon on numerous national highways traversing the Tarim basin has become a considerable concern [35].

2.2. Data Sources

This research employed a multi-source approach, integrating data from various sources, including soil and re-analysis data (

Table 1. Data sources.

Indicator	Indicator Content	Spatial Resolution	Data Sources	Unit	Indicator Processing
X1	Soil organic carbon content	250 m	OpenLandMap	g/kg	negative
X2	Soil water content	250 m	OpenLandMap	%	negative
X3	Soil sand content	250 m	OpenLandMap	% (kg/kg)	positive
X4	Land-use type	1000 m	Resources and Environmental Science and Data Center, Chinese Academy of Sciences	—	positive
X5	NDVI	1000 m	Earthdata	—	negative
X6	Precipitation	2.5′	TERRACLIMATE	mm	negative
X7	Potential evapotranspiration	2.5′	TERRACLIMATE	mm	positive
X8	RDP	0.1°	European Centre for Medium-Range Weather Forecasts (ECMWF)	VU	positive

). The soil data were obtained from OpenLandMap (https://gitlab.com/openlandmap, accessed on 9 June 2023), which provides continuous-type raster data with a spatial resolution of 250 m at six standard depths (0, 10, 30, 60, 100, and 200 cm). The R² values for the simulated soil organic carbon content, soil water content, and soil sand content relative to the measured values were 83.4%, 95.5%, and 90.8%, respectively. Meteorological variables include rainfall, potential evapotranspiration, and wind speed. The rainfall and potential evapotranspiration data were obtained from TERRACLIMATE with a spatial resolution of 2.5′ and high accuracy. The Pearson’s correlation coefficient of the precipitation, using GHCN (Global Historical Climatology Network) data, was 90%, with an average absolute error of 9.1%, and that of the potential evapotranspiration data from FLUXNET was 77%, with an average absolute error of 8.3% [36]. The wind speed data were derived from ERA5 re-analysis data, which had a temporal resolution of hours and a spatial resolution of 0.1°. These data exhibited a high degree of fit to the measured data from meteorological stations, and are more applicable than the NECP data in the Chinese region [37]. The normalized vegetation index (NDVI) data were obtained from MOD13A2 with a global precision of ±0.025. NDVI values less than 0 were assigned null values to exclude ice/snow regions. To ensure the timeliness of the results, the mean values of rainfall, potential evapotranspiration, RDP, and NDVI from 2001 to 2020 were calculated and subsequently used in the modeling process.

2.3. Research Methodology

The aeolian environment can be quantified by combining wind power strength and sand abundance. The RDP indicates the region’s potential sand transport capacity, which can be used to characterize the strength of wind power. Soil conditions, vegetation cover, precipitation, and potential evapotranspiration indirectly affect sand abundance. The land-use type quantifies the risk of aeolian dispersion in the region. These seven indices can comprehensively characterize the abundance of sand sources (Figure 2).

2.3.1. Diagnosis of Multicollinearity in Evaluation Indicators

Before evaluating the model, it is essential to diagnose multicollinearity, a crucial aspect of the analysis [38]. Correlations exist between the indicators, and they exert influence upon one another. The covariance of the indicators will affect the accuracy of the evaluation results. Therefore, assessing factor independence and eliminating multiple covariances are prerequisites for obtaining scientific evaluation results. The variance inflation factor (VIF) can be employed to ascertain the extent of multicollinearity between evaluation indicators.

$$VI{F}_i={\displaystyle \frac{1}{1-R_i^2}},$$

(1)

Here, VIF_i is the variance inflation factor of indicator i, and R_i² is the coefficient of determination of indicator i. According to the VIF value, the covariance was classified as no covariance (0 < VIF ≤ 5), weak covariance (5 < VIF ≤ 10), moderate covariance (10 < VIF ≤ 100), and severe covariance (VIF > 100), according to the VIF value. Following the diagnosis of multiple covariance (Figure 3), the VIF values of all indicators were found to be less than 10, indicating that none of the indicators exhibited severe covariance. This suggests that the indicator system is both scientific and reasonable.

2.3.2. Wind Power and Sand Source Abundance Assessment Model and Classification of Aeolian Environments

The natural disaster risk assessment method serves as a guiding framework for the construction of the sand abundance index in this study. In light of the scientific rigor, logical coherence, and simplicity of the evaluation model, this study employs the “two-factor theory” [39] and integrates the seven aforementioned indicators to characterize regional sand abundance comprehensively. Each continuous indicator is classified into five levels using the natural breakpoint method. All indicators are treated as positive, with larger values indicating a higher risk of wind–sand dispersion.

$$san{d}_m=\sqrt[7]{organic\times water\times sand\times LUCC\times NDVI\times pre\times pet},$$

(2)

Here, sand_m is the sand source richness class, organic is the soil organic carbon content class, water is the soil water content class, sand is the soil sand content class, LUCC is the land-use type class, NDVI is the NDVI class, pre is the precipitation class, and pet is the potential evapotranspiration class.

$$DP={{\displaystyle \sum }}_{j=1}^n{V}_t^2\times \left(V_i-V_t\right)\times t_i\left(t_i={\displaystyle \frac{1}{N}}, V_i\ge V_t\right)$$

(3)

The DP (Drift Potential) variable represents the sand transport potential, and the critical starting wind speed (V_t) is set to 6.0 ms⁻¹ [40,41]. The variable V_i denotes the wind speed of the ith observation, while N represents the total number of 1a observations. Finally, n denotes the number of sand-starting winds.

Wind_p = RDP,

(4)

where Wind_p is the wind-dynamic condition and RDP is the synthetic sand transport potential rating.

$$AT=10\times win{d}_p+san{d}_m,$$

(5)

Here, AT is the type of aeolian environment, and the wind-dynamic conditions and sand abundance classes are divided into five levels, where levels 1, 2, 3, 4, and 5 correspond to the degree of wind or sand abundance as follows: no or light, light, moderate, medium, and very heavy, respectively. The wind power condition level is multiplied by 10 and added to the sand source richness level, resulting in a combined value for wind power and sand source. This value is then used to determine the AT level. In theory, there are 25 distinct aeolian environment types, with the first indicating the strength of the wind power and the second indicating the amount of the sand source. The greater the value of the aeolian environment type, the more pronounced the trend of wind power and sand source abundance. The lowest wind power and lowest sand source abundance are observed at a value of 11, while the highest wind power and highest sand source abundance are observed at 55.

2.3.3. Aeolian Environment Regionalization in Xinjiang

Zoning Objectives

In light of the considerable variability in the spatial distribution of aeolian environments across the entire Xinjiang region and the multitude of complex and diverse underlying causes, a scientific, comprehensive, integrated, and coordinated zoning approach represents a fundamental prerequisite for the effective implementation of disaster prevention and mitigation measures. Consequently, aeolian environment zoning was established when the specific characteristics of the aeolian environment were elucidated, which fully integrated considerations of the natural climate, geomorphological patterns, and geological conditions. This serves as a scientific reference and practical guidance for relevant departments in the formulation of sand prevention and sand control planning.

Zoning Principles

(1) The principle of comprehensive evaluation indicators is a fundamental tenet of scientific inquiry. To formulate the aeolian environment zoning scientifically and reasonably, it is necessary to select many comprehensive and objective evaluation indices. This ensures that the regional wind energy environment and sand and dust environment are adequately characterized. To do this, it is necessary to study the existing literature and consider expert opinions [42].

(2) The principle of similarity of aeolian environment. Under the first law of geography, all things are correlated, wherein similar things are more closely related [43]. Given the similarity of vegetation, soil, climate, geomorphology, and other conditions within a given area, it can be reasonably assumed that the aeolian environment within the same control area will also exhibit similar characteristics.

(3) The principle of consistency of sand prevention measures. It is recommended to adhere to the principles of sand prevention and sand control according to local conditions and hazards, consider the similarity of the aeolian environment in the region, determine the main characteristics of the elements of the aeolian environment within the zoning area, grasp the critical contradictions of sand prevention and sand control, and implement the same mode of sand prevention and configuration within the same zoning area. This helps relevant departments to carry out their work in a unified manner.

(4) Expert opinions and the principle of consistency of causes. The same zoning unit should have a high degree of similarity in the conditions for the occurrence and development of wind and sand activities, the mode and intensity of wind and sand activities, and wind and sand prevention and control measures, which is an important factor to ensure the scientific nature of zoning.

(5) The principle of comprehensive factors. Many factors are related to the aeolian environment. To make an extensive and correct diagnosis of regional differences, various related factors should be analyzed comprehensively as much as possible to avoid generalization or the omission of important information.

(6) The principle of dominant factors is crucial in zoning for wind and sand prevention and control. It emphasizes the importance of identifying the main contradictions when analyzing relevant problems. This process of determining the dominant factors in the aeolian environment facilitates the development of targeted and effective response or prevention strategies.

Zoning Methodology

This study presents a methodology for determining zoning boundaries at all levels, based on zoning principles and evaluating the relevant indices to create an aeolian environment zoning system. The zoning system presented in this study is divided into four levels of zoning. The first-level zoning is divided into the temperate arid and semi-arid wind and sand zone on the northern border and the warm temperate extreme arid wind and sand zone on the southern border [44]. The natural climate and geomorphological conditions influence the regional aeolian environmental conditions and the degree of wind and sand hazards. These conditions vary considerably across the region and, according to the “Geomorphology of Xinjiang and its Environmental Effects”, subzones were further divided based on the first-level zoning. The Altai–Beitashan subzone, the western Dzungar Mountain subzone, the Dzungar basin subzone, the northern slope of the Tianshan Mountains subzone, the southern slope of the Tianshan Mountains subzone, the Tarim basin subzone, and the Kunlun Mountains–Altshanshan Mountains subzone constitute the subzones of the Kunlun Mountains–Altan Mountains subregion.

Based on the ERA5 re-analysis data, the annual dominant wind direction in Xinjiang was employed as the foundation for the division of the third-level zoning, with the boundaries of the third-level zoning determined based on the second-level zoning. The nomenclature of the third-level zoning is based on the combination of a “middle (small) geographic unit name”, a “geomorphology type”, and a “dominant wind direction”. This approach highlights the geographic location, geomorphology type, and dominant wind direction. The fourth-level zoning was established based on the third-level zoning under the principles of comprehensiveness, similarity of aeolian environments, and consistency of sand prevention measures, considering the type of regional aeolian environments and the relevant indices characterizing these environments. The nomenclature of the fourth-level zoning system is based on the principle of the “middle (small) geographic unit name” + “geomorphology type” + “dominant wind direction” + “aeolian environment type”. This approach allows for a more detailed and nuanced representation of the regional aeolian environment, extending beyond the third-level zoning system.

3. Results

3.1. Spatial Distribution of Aeolian Environmental Types in Xinjiang

The mean annual RDP values across the entire Xinjiang region range from 0 to 1176 VU, exhibiting a spatial distribution characterized by high values in the eastern region and low values in the western region, as well as high values in the basin and low values in the mountains (Figure 4a). The wind energy environment in the area is dominated by low-energy conditions (RDP< 200 VU), which account for 91.77% of the total. Medium-energy conditions (200 ≤ RDP ≤ 400 VU) and high-energy conditions (RDP > 400 VU) collectively account for 8.23% of the total. The medium- and high-energy areas are primarily located in the Santang–Nao Mao low hills, Tuha basin, Lop Nor poor-quality salt flats, eastern Tarim basin, northern middle-eastern Kunlun Mountains, and significant wind areas.

The sand source richness is the material source of wind–sand activities, and its spatial heterogeneity is closely related to land-use types (Figure 4b). The low value of sand source abundance is mainly distributed in mountainous areas, oases, and along rivers, with high vegetation cover, good moisture conditions, and soil stability. The wind and sand control projects in these places are relatively well constructed, lacking the sand material required for wind and sand activities. The types of sand corresponding to the high value of sand source abundance are flowing semi-fixed sand and fixed semi-fixed sand. The abundance of sand sources provides a substantial material basis for wind–sand activities, yet frequent human disturbances exacerbate the desertification process. The natural breakpoint method divides the sand source richness value into five levels, and the overall sand source grade is divided into two categories, levels 2 and 3, which account for 32.93%, 23.38%, 23%, and 20.68%, respectively, of the total image elements.

The quantitative characterization of the spatial distribution of wind–sand environments can be achieved by analyzing the type of aeolian environment. Complex geomorphological patterns result in significant regional aeolian environmental variations. These variations are meridional, with an overall increasing trend observed with increasing longitude (Figure 4d). The high value of the aeolian environment type corresponds to regions with stronger winds and richer sand sources. These are mainly located in the Santang–Nao Mao low hills, the Hashun Gobi, Kuruktag, the eastern Taklamakan desert, and the northern part of the middle-eastern Kunlun Mountains. The regional subsurface is mostly the Gobi and the flowing desert, and strong wind is a typical feature of this region. In contrast, the central and western Taklamakan desert and the Gurbantunggut desert have many sand sources, but the wind force is drastically scaled down compared with the leading wind areas. Consequently, the aeolian environment type value is low. Areas with low values of the aeolian environment type are associated with low values of sand abundance, where soil moisture is a dominant factor.

3.2. Aeolian Environmental Regionalization Results

The results of aeolian environmental regionalization at various levels are presented in Figure 5. Following the objectives and principles of zoning, the methodology employed, and expert opinions [42], two first-level zones were delineated using the Tianshan Mountains as a demarcation line. Furthermore, 7 s-level zones were established based on the large geomorphologic unit of Xinjiang, 22 third-level zones were delineated based on the dominant wind direction, and 31 fourth-level zones were delineated based on the type of aeolian environment (Figure 5). The names of the zones at each level are provided in

Table 2. Xinjiang aeolian environmental regionalization program.

First Level of Zoning	Second Level of Zoning	Third Level of Zoning	Fourth Level of Zoning	No.
Temperate arid and semi-arid wind and sandy areas in northern Xinjiang region	Altay–Beitashan subregion	Altai Mountains and the Jundong hills + Mountains and hills + Northerly and easterly wind areas	Altai Mountains and the Jundong hills + Mountains and hills + Northerly and easterly wind areas + Weak winds and less sandy areas	1
		Beita Mountain–Santang–Nao Mao Lake basin + Mountains and basin + Northerly and westerly wind areas	Northern Beita Mountains + Mountains + Westerly wind areas + Weak winds and less sandy areas	2
			Santang–Nao Mao Lake basin + Basin + Northerly and westerly wind areas + Strong winds and less sandy areas	3
	Junggar basin subregion	Southeastern Junggar basin + Basin + Northerly and westerly wind areas	Gurbantunggut desert + Desert + Northerly and westerly wind areas + Strong winds and less sandy areas	4
			Southeastern Junggar basin + Basin + Northerly and westerly wind areas + Weak winds and less sandy areas	5
		Ulungu River basin + Basin + Southerly and easterly wind areas	Ulungu River basin + Basin + Southerly and easterly wind areas + Weak winds and less sandy areas	6
		Gurbantunggut desert + Desert + Northerly and easterly wind areas	Gurbantunggut desert + Desert + Northerly and easterly wind areas + Weak winds and more sandy areas	7
		Southwestern Junggar basin + Basin + Northerly and easterly wind areas	Southwestern Junggar basin + Basin + Northerly and easterly wind areas + moderate winds and less sandy areas	8
			Junggar basin + Basin + Northerly and easterly wind areas + Strong winds and less sandy areas	9
		Northern Junggar basin + Basin + Northerly and westerly wind areas	Junggar basin + Basin + Northerly and westerly wind areas + Strong winds and less sandy areas	10
			Irtysh River valley + Valley + Northerly and westerly wind areas + Strong winds and less sandy areas	11
	Mountainous subregion of western Junggar	Tacheng district–Hoboksar basin + Basin + Northerly and westerly wind areas	Hoboksar basin + Basin Northerly and westerly wind areas + Strong winds and less sandy areas	12
			Tacheng Laofengkou basin + Basin + Northerly and westerly wind areas + Moderate winds and less sandy areas	13
		Western Junggar Mountains + Mountain + Complex wind region	Western mountain region of the Junggar basin + Mountain + Complex wind areas + Weak winds and without sand areas	14
	Tianshan north slope subregion	Northern Tianshan Mountains + Mountain + Southerly and westerly wind areas	North slope of the Tianshan Mountains + Mountains + Complex wind areas + Weak winds and without sand areas	15
		Northern Tianshan Mountains + Mountain + Southerly and westerly wind areas	Northern Tianshan Mountains + Mountains + Southerly and westerly wind areas + Strong winds and less sandy areas	16
Warm-temperate extreme arid sandy wind region in southern Xinjiang	Tianshan South Slope subregion	Yandun wind area (southeast of Hami) − Southern Gobi of Hami + Gobi + Southerly and easterly wind areas	Yandun wind area (southeast of Hami) − Southern Gobi of Hami + Gobi + Southerly and easterly wind areas + Strong winds and less sandy areas	17
		Southern edge of Tianshan Mountains + Mountain + Northerly and westerly wind areas	100 km gale area + Low hills and plains + Northerly and westerly wind areas + Strong winds and less sandy areas	18
			South Tianshan Mountains + Mountains + Northerly and westerly wind areas + Weak winds and without sand areas	20
		Kuruktag + Mountain + Northerly and easterly wind areas	Kuruktag + Mountains + Northerly and easterly wind areas + Moderate winds and less sandy areas	19
	Tarim basin subregion	Southern piedmont of Tianshan plain + Plain + Southerly and westerly wind areas	Southern piedmont of Tianshan plain + Plain + Southerly and westerly wind areas + Weak winds and less sandy areas	21
		Northern Taklamakan desert + Desert + Easterly wind area	Northern Taklamakan desert + Desert + Easterly wind area + Moderate winds and more sandy areas	22
			Northern Taklamakan desert + Desert + Easterly wind area + strong winds and less sandy areas	23
		Kumutage desert + Desert + Southerly wind area	Kumutage desert + Desert + Southerly wind area + Moderate winds and more sandy areas	25
		Southwestern Tarim basin + Basin + Easterly wind area	Southwestern Tarim basin + Basin + Easterly wind area + Weak winds and less sandy areas	27
		Western margin of Tarim basin + Basin + Northerly and westerly wind areas	Western margin of Tarim basin + Basin + Northerly and westerly wind areas + Weak winds and less sandy areas	29
		Tarim basin + Basin + Northerly and easterly wind areas	Eastern margin of the Tarim basin + Basin + Northerly and easterly wind areas + Strong winds and more sandy areas	24
			Central Tarim basin + Basin Northerly and easterly wind areas + Moderate winds and more sandy areas	26
			Yarkant River basin + Basin + Northerly and easterly wind areas + Weak winds and less sandy areas	28
	Kunlun–Altun Mountains subregion	Kunlun Mountain–Altun Mountain + Mountain + Easterly and westerly wind areas	Kunlun Mountain–Altun Mountain + Mountain + Easterly and westerly wind areas + Weak winds and less sandy areas	30
		Northeastern central Kunlun Mountains and Qiangtang plateau + Mountain and plateau + Complex wind areas	Northeastern central Kunlun Mountains and Qiangtang plateau + Mountains and plateau + Complex wind areas + Strong winds and less sandy areas	31

.

4. Discussion

4.1. Causes of Spatial Differentiation of Aeolian Environments in Xinjiang

To ensure the sustainability of critical infrastructure, systematically clarifying the causes of the spatial differentiation of the aeolian environment in Xinjiang can provide a theoretical basis for developing sand prevention and hazard sand control. In general, the unique topographic and geomorphic patterns of Xinjiang and the aeolian environment have a long-term mutual feedback effect, which is the driving force for the formation and development of the aeolian environment.

The landforms of Xinjiang are distinguished by significant undulations, with altitudes ranging from −155 to 7530 m. The “three mountains and two basins” are the prevailing characteristics of the landforms in Xinjiang. Atmospheric circulation and the mountain–basin system influence Xinjiang’s aeolian environment. The Tibetan plateau, the Pamir plateau, and the Tien Shan Mountains are the root causes of the basin’s extremely arid climate and desert formation [45], and the westerly circulation system and the Mongolian high-pressure system are external factors that influence wind and sand movement [46]. The mountain–basin system in Xinjiang is distinctive, resulting in a complex and diverse near-surface atmospheric motion. The Tian Shan obstructs the entry of the Arctic Ocean airflow, while the Tibetan plateau and Kunlun Mountains impede the entry of the Indian Ocean airflow [47].

Throughout the year, mainly westerly airflow enters the Junggar basin through the mountain passes in western and northwestern Xinjiang, which then arrives at the junction between the eastern end of the coccyx of Bogda Mountain and the western end of Barkun Mountain and penetrates deeper into the Tarim basin through the eastern, western, and central irrigation regions [48]. This is an essential multiple wind region and a critical wind power base construction area. Sand supply is the most important condition in the desertification process, and Xinjiang is rich in sandy materials, with large areas of desert and Gobi [49]. In conclusion, Xinjiang is characterized by an aeolian environment, influenced by the geomorphic pattern determined by the mountain–basin system, the widely dispersed sediments in the basin, and the atmospheric circulation. In addition, the aeolian environment promotes the development and evolution of geomorphological patterns. The two significant basins in Xinjiang are characterized by almost opposite directions of topographic dip and a dominant wind direction [48]. The direction of the topographic dip determines the direction of fluvial sediment transport [50], while the dominant wind direction determines the direction of wind-formed sediment transport [51]. Therefore, the peculiar tectonic genesis and atmospheric circulation patterns in Xinjiang determine the complex geological macrocycle processes, confirming the complexity and multi-source origin of subsurface sand materials.

4.2. Countermeasures against Sand Prevention in Typical Aeolian Environment Regionalization

4.2.1. Measures for Ecological Management in the Subregion of Aeolian Environments

Desert areas have developed distinctive geomorphological landscapes and perform particular ecological service functions within the ecosystem. To address the specific characteristics of the regional aeolian environment, a series of environmental management measures have been proposed for each secondary zoning area (Figure 6a).

(1) The Altay–Beitashan subregion should be mainly protected by conservation and management. The subarea of the Altay Mountains is the main body, characterized by mountain elevation, precipitation, and vegetation cover; the overall wind erosion activity is weak and mainly occurs in the foothills and hilly plains, which should be protected by natural vegetation, for which artificial auxiliary restoration of vegetation is the most important activity. At the same time, the wind power in the low hills of Santang–Nao Mao Lake is extreme, wind erosion is intense, and, due to the recent construction of a photovoltaic power plant on the lower bedding surface of the intrusion, it has further intensified. Therefore, attention should be paid to the setting of the local conditions when developing sand prevention and sand control engineering measures.

(2) The Junggar basin subregion has a complex sandy and windy environment with various land-use types, and comprehensive management should be the main focus. The Gurbantunggut desert dominates this subregion. It includes the Erqis River basin and the urban agglomeration on the northern slope of Tianshan Mountain, among other features. At the same time, unsustainable human economic activities are the biggest threat to the relatively stable ecosystem, and the fragile biological crust plays a significant role in preventing the land from becoming sandy. Therefore, the reclamation of sandy areas and the ecological restoration of fallow lands, the improvement of oasis protection forests and the construction of technical and prevention systems, the strengthening of the reconstruction of degraded vegetation on the periphery of oases, and the reclamation of activated sand dunes on the edges of deserts should be accelerated in response to major regional conflicts.

(3) The overall soil and water conditions in the mountainous subregion of western Junggar are relatively good, and the primary focus should be on sealing, conservation, and management. The Tacheng Mountain basin is the center of the mountains, and the overall vegetation cover is high; the basin plain precipitation reaches up to 300 mm, the oasis protection system is perfect, the risk of land desertification is low, and the overall conservation and management of conservation are good. On the other hand, the wind power in the Tacheng old wind gap zone is extreme, and windy weather of grade 8 or above can reach a frequency of 180 days a year; therefore, the critical task in this region is wind prevention.

(4) The subregion of the northern slopes of the Tianshan Mountains and the subregion of the southern slopes of the Tianshan Mountains have high precipitation and various landscape types, and they should be closed for conservation and afforestation. The Tianshan is a “wet island” in the arid region of northwest China, and the northern Tianshan is particularly prominent, with extensive forests and grasslands, ice and snow cover, and better soil moisture conditions. Although the moisture conditions in southern Tianshan are worse than those in northern Tianshan, the risk of land desertification is low in most parts of the region, without anthropogenic disturbances caused by industrial and mining development and infrastructure construction. Wind erosion and sand deposition, on the other hand, are prevalent in the plains of the intermountain basin. This subregion contains national and autonomous region-level prohibited development zones, forest parks, scenic spots, and so on. Closure, conservation, and afforestation are long-term tasks in the region.

(5) The Tarim basin subregion is characterized by extensive deserts and widely varying aeolian environments, and comprehensive management should be the focus. Taking the Taklamakan desert as the core, there is a 1400 km aeolian front in the south, which connects several oases and is a crucial area for sand prevention and control; the Tarim River basin in the north is an irreplaceable ecological corridor; and in the east and west, there are channels for the gusty circulation of the basin to enter and play a role in the deserts and their surroundings. Therefore, protecting the oasis in the region requires reforestation and management, the treatment and repair of river outlets, the care and maintenance of river corridors, and sealing and protection of the deserts.

(6) The Kunlun Mountains–Altun Mountains subregion should be mainly closed for conservation. More than 50% of the area of this subregion is covered by the Gobi cold desert and barren rocks, including the Kumukuli desert and the Bulunkou desert. The Arjinshan Nature Reserve, the Middle Kunlun Mountains Nature Reserve, and the Tashkurgan Precious Animals Nature Reserve have been established in this subregion, and the degree of human disturbance is relatively low; however, due to the scarcity of water resources and the unfavorable conditions of high and low temperatures, the region’s natural restoration capacity is weak, and the implementation of closure and conservation measures is the key to realizing sustainable development.

4.2.2. Structural Models of Sand Control Systems for Roads in Sandy Areas

Xinjiang is a vast area with frequent occurrences of sand and wind activity, and sand and wind disasters have become the primary threat to the safe operation of infrastructure. However, different types of infrastructure (railroads, highways, irrigation canals, oilfield bases, and so on) have different disaster conditions, sand prevention priorities, and sand prevention measures. As such, the sand prevention and control model is not universally applicable; instead, it should be developed for specific disaster objects to set up preventive measures according to the hazards and the structure of the sand prevention system according to the local conditions. Highways play a pivotal role in the transportation of resources, movement of people, emergency security, economic connectivity, and other critical functions. Therefore, they are a primary focus of sandstorm prevention and control efforts. The technical specifications of highways are exacting, the types of ancillary facilities are numerous, and the factors precipitating regional wind and sand disasters are intricate and multifaceted. Consequently, it is imperative to propose a regional highway sand prevention system structure model to mitigate highway wind and sand hazards.

The structure model of the highway and prevention system should be oriented to different types of aeolian environments in order to solve the principal contradiction flexibly, combining the elements of “blocking, fixing, transporting, and guiding” to achieve the goal of practicality and economy. A sand prevention system structure model is proposed based on the assessment results of the aeolian environment types (Figure 7). The aeolian environment zoning results can inform the formulation of a sand prevention system structure model, with the aeolian environment types in the fourth-level zoning serving as a reference. In the case of weak wind and less sand (Figure 7a), sand prevention measures such as the grass square lattice can be primarily implemented in nature. This type of sand prevention measure can block the transportation of sand material and ensure a long-term effect.

In the case of a weak aeolian environment (Figure 7b), where the wind is weak but the sand source is abundant, a combination of blocking and fixed sand control measures can be employed. This may include vertical sand barriers and grass squares, among other options. In general, blocking-type sand control measures are set up outside to prevent the sand source from moving forward, while fixed-type sand control measures prevent an area from becoming covered and, in contrast, are set up on the inside of an area. In the case of a strong wind and a limited sand source (Figure 7c), it is particularly challenging to accumulate sand in the area in question. In such instances, it is advisable to prioritize wind-blocking and sand-transferring control measures, such as installing a downward wind-guiding project. In the case of a strong aeolian environment (Figure 7d), characterized by a strong wind and abundant sand sources, the aeolian environment is complex and subject to change. In light of the specific circumstances of the region, the sand prevention measures of blocking, fixing, and guiding should be employed flexibly.

4.3. Enlightenment

Desertification represents a significant global ecological, environmental, and socio-economic challenge. It not only results in the deterioration of the ecological environment but also contributes to a reduction in agricultural productivity and incomes, ultimately impacting the normal production and quality of life of people. The countries of the Sahel (Senegal, Mauritania, Mali, Burkina Faso, Niger, Nigeria, Chad, Sudan, South Sudan, Ethiopia, and Eritrea), which collectively represent a population of nearly 500 million people, are subjected to the hot and dry winds of the Sahara desert on a year-round basis. This makes them the most drought-prone region in the world. The region is particularly susceptible to desertification and sandstorms. In the Sahel, the aeolian environment constrains the growth of vegetation, heightens the susceptibility of the land, and has a detrimental impact on the ecosystems, necessitating the implementation of targeted preventive and control measures in this region.

The regionalization of the aeolian environment in Xinjiang can provide valuable insights for countries in the Sahel region that are facing threats from wind and sand. This information can be utilized to enhance the comprehension of, and strategies for the mitigation of, wind and sand-related risks. A zoning approach, based on regional variations in aeolian environment types, can be employed to delineate areas susceptible to these hazards. Furthermore, it permits the implementation of locally tailored ecological restoration and engineering measures for the prevention and control of sand.

5. Conclusions

The Xinjiang aeolian environment regionalization aims to provide a global and systematic scientific basis for relevant departments to formulate sand prevention and control plans. This study synthesized multi-source data to assess the wind energy environment, sand and dust environment, and aeolian environment types, then formulated a four-level zoning scheme for the environment of Xinjiang and put forward systematic sand prevention suggestions for typical aeolian areas. The results show the following:

(1)

Significant spatial differences characterize the aeolian environment and its types in the Xinjiang region. The wind energy environment throughout the Xinjiang region is high in the east, low in the west, high in the basins, and low in the mountains. The overall wind energy environment of the whole region is dominated by low energy (RDP < 200VU; 91.77%). The spatial variability of the sand material base across Xinjiang is closely related to land-use types, with uneven distribution of soil moisture being the dominant cause.

(2)

A four-level zoning scheme was formulated for Xinjiang’s aeolian environment. Two level 1 zones were demarcated, with Tianshan Mountain as the demarcation line; seven level 2 zones were demarcated based on the significant geomorphological units of Xinjiang; 22 level 3 zones were demarcated based on the dominant wind direction; and 31 level 4 zones were demarcated based on the aeolian type.

(3)

Based on the secondary zoning’s aeolian environment characteristics and sustainable development priorities, ecological management measures of sealing and conservation, management and nourishment, afforestation and nourishment, and comprehensive management were proposed. According to the differences between regional aeolian environment types, the engineering configuration mode was divided into four categories: fixed-type sand control measures, blocking and fixing sand control measures, wind-blocking and sand-transferring sand control measures, and flexible combinations of blocking, fixing, and sand-transferring sand control measures.

It is important to note that there are still some challenges, such as the precision issue, given the multitude of factors, including climate, topography, and vegetation, that influence wind and sand activities. This results in difficulties in acquiring comprehensive and accurate data. Furthermore, the study did not fully address the dynamic changes of wind and sand due to technical limitations, which may affect the study’s timeliness. Furthermore, international collaboration and the exchange of knowledge must be reinforced, including sophisticated international theories and techniques of aeolian environment zoning. Through technological innovation, multidisciplinary and crossdisciplinary cooperation, and the reinforcement of policy application, this field is anticipated to yield enhanced scientific and effective solutions for the prevention and control of wind and sand disasters.