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Journal of Resources and Ecology >

2023 , Vol. 14 >Issue 4: 692 - 705

DOI: https://doi.org/10.5814/j.issn.1674-764x.2023.04.002

Environmental Management of Mines

Spatial and Temporal Variation Characteristics of Wind Erosion Climate Erosivity in the Arid Desert Region of Northwestern China

  • MA Wenzhang , 1 ,
  • YANG Jin 2 ,
  • DING Sirui 1 ,
  • SHI Changqing , 1, * ,
  • ZHAO Tingning , 1, *
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  • 1. School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
  • 2. Beijing Institute of Water, Beijing 100048, China;
*SHI Changqing, E-mail: ;
ZHAO Tingning, E-mail:

MA Wenzhang, E-mail:

Received date: 2023-01-15

  Accepted date: 2023-04-20

  Online published: 2023-07-14

Supported by

Key Research and Development Program of China(2017YFC0504403)

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Abstract

Soil wind erosion is an important factor that inhibits social activities and economic development in the arid desert region of northwestern China. In order to reveal the distribution of soil wind erosion climate erosivity in the arid desert region of northwestern China, the spatial and temporal variation and transfer characteristics of wind erosion climate erosivity in the region were evaluated by referring to China’s regional ground long-time series meteorological element driving data, and applying the ArcGIS software analysis. The study results show that: (1) Against a backdrop that such meteorological factors as precipitation amount, wind speed, and average temperature over multiple years all increase progressively decade by decade, the wind erosion climate erosivity in the northwest arid desert region is decreasing as a whole. The C values of most areas are within the range of 0 to 100. However, the climate erosivity in the hinterland and a few areas is increasing, with C values higher than 150. (2) The monthly variation of the C value varies significantly. The greatest variation occurs in spring and summer, followed by the variation in winter, while the slightest variation occurs in autumn. Through the abrupt change test, it is found that the wind erosion climate erosivity in spring has the strongest variation, with four abrupt change points and a pattern of long-term fluctuating decline. (3) The soil wind erosion in the region gradually decreases from the hinterland to the peripheral areas, with the areas highly affected by erosion increasing yearly. (4) The spatial-temporal transfer and variation of wind erosion climate erosivity present an overall pattern of slight decrease. However, in some areas, they increase or show an apparent trend of increase. The study results have provided relevant theoretical evidence and scientific support for preventing and controlling wind‒sand disasters in the arid desert region of northwestern China.

Key words： wind erosion; climatic erosivity; northwest arid desert region

Cite this article

MA Wenzhang , YANG Jin , DING Sirui , SHI Changqing , ZHAO Tingning . Spatial and Temporal Variation Characteristics of Wind Erosion Climate Erosivity in the Arid Desert Region of Northwestern China[J]. Journal of Resources and Ecology, 2023 , 14(4) : 692 -705 . DOI: 10.5814/j.issn.1674-764x.2023.04.002

1 Introduction

The natural environment, being the prerequisite for the survival of human society, bears the weight of providing the spatial foundation for social material life and sustainable development (Hu et al., 2022). As the most complex challenge that humankind is facing now, climate change has become a hot topic being studied globally (Chen et al., 2022). Due to the changes in the climate conditions of precipitation, wind speed, and light radiation, the structure and functions of the natural environment have been significantly changed. Because of the differences in meteorological elements’ fluctuating variation characteristics and geographical distribution patterns (Zhang et al., 2023), the regional climate features are also complex, multiple, and spatially heterogeneous.
Wind erosion is the most natural phenomenon of land degradation and desertification in arid and semi-arid areas, especially in the vast desert and peripheral areas, with distinctive characteristics of severe damage and difficult measurement (Merrill et al., 1999). Specifically, it refers to the comprehensive natural geographical process in which near- surface soil particles are abraded, eroded, and transferred by airflow or gas-solid two-phase flow (Dang et al., 2019). This process is primarily subject to regional climate conditions. Wind erosion climate erosivity (Lou et al., 2019) is the primary index to measure the potential degree of soil wind erosion affected by climate conditions in large-scale areas. It can reveal the soil desertification intensity quantitatively. At the same time, it can predict the development trend of future wind erosion. Currently, there are three model calculation methods in relevant studies: 1) The humidity index‒based mathematical formula (Chepil et al., 1962) of climate erosivity introduced in the last century based on related research (Chepil and Milne, 1939). 2) The mathematical formula of wind erosion climate erosivity with a relatively simple calculation (Li et al., 2018), easy data acquisition, and more robust applicability derived through modifying the formula as mentioned above. 3) The Skidmore formula (Skidmore, 1986) introduced by some scholars. Although this formula has a reliable theoretical foundation, its data are hard to obtain. So, a high-quality indicator is required to use this formula. Therefore, the FAO formula is still the primary method to evaluate and calculate the wind erosion climate erosivity in arid areas (Chen and Dong, 2020).
The response of spatial and temporal dynamics of wind erosion erosivity to regional natural climate changes is the primary research direction of wind erosion climate erosivity (Liu et al., 2022). In a study of climate erosivity in arid and semi-arid areas based on the meteorological data from 1951 to 1980, the FAO formula was used in China for the first time (Dong and Kang, 1994). The study shows that the C values of some parts of the northwest region where soil wind erosion is likely to occur are extremely high. In contrast, the erosivity levels of other parts of the region are moderate. Some studies have analyzed and calculated the wind erosion erosivity in large-scale agriculture and pasture-interlaced areas in northern China (Wang et al., 2005). These studies show that seasonal changes also highly influence wind erosion erosivity. The degrees of wind erosion in spring and winter, when rainfall is scarce, windy days are relatively frequent, and the ground surfaces of this region are mostly exposed, are much higher than the degrees in summer and autumn. When relatively small-scale geographical areas are used as the study object for analysis, the complex structure and abrupt change feature of wind erosion climate erosivity under multiple time scales have been revealed through the wavelet function (Zou et al., 2011). It is found that the C value has apparent periodic phase fluctuations. Wang et al. (2021b) have studied the soil wind erosion potential and desertification evolution feature in Xinjiang. They found that the wind erosion erosivity in this area had presented, as a whole, an apparent fluctuating decrease trend over the past 50 years, with two stages of a rebound during the same period. However, the wind erosion climate erosivity in this area’s primary wind erosion geomorphic zones has presented an increasing trend.
The geographical and meteorological distribution of the northwest arid desert region covers the westerly climate zone, plateau climate zone, part of the southeast monsoon zone, and the monsoon zone edge. These zones are the primary sensitive and complex areas of climate change (Wang et al., 2021a; Xie et al., 2021), where the meteorological elements distribute very unevenly. Also, this region is the primary distribution area where deserts and sand land in China are concentrated. In most parts of this region, there is an arid climate and shortage of precipitation, with a fragile ecosystem that is vulnerable to the impact of climate change (Wang et al., 2022a). Not only does soil wind erosion in the arid desert area directly impacts the regional ecological environment quality and economic development, but it also affects the ecological environment quality and sustainable development of adjacent areas and even the whole country. Therefore, analyzing and determining the distribution characteristics of wind erosion climate erosivity in the southwest arid desert region is necessary. It can provide fundamental guidance and suggestions for promoting regional social and economic development.
In general, although there have already been many studies on wind erosion climate erosivity, they have mainly focused on individual administrative regions, areas with extreme wind and sand phenomena, or areas with interlaced agriculture and pasture distribution. Little research has been carried out to investigate large-scale natural weather zones. No study has yet been conducted to assess the wind erosion climate erosivity in the northwest arid desert region. Also, the wind erosion variation characteristics in this region are less known, especially under the climate change trend of global warming and the co-existence of dry and wet seasons with an increasingly pronounced contrast. The economic development of the arid desert areas has been severely affected by natural conditions, resulting in lagging behind social development. Thus, these regions are essential areas where people’s living standards should be improved, and social equity should be promoted. So, assessing the wind erosion climate erosivity in these areas is of particular importance. On the basis of long-term series ground meteorological element driving data and ArcGIS interpolation analysis, the potential occurrence condition of soil wind erosion in arid desert areas has been explored by using the FAO method to calculate the wind erosion erosivity in those areas. This study has been performed with the following purposes: 1) Clarifying the distribution features of meteorological elements of the large-scale natural meteorological zones in this region; 2) Using the meteorological element data to assess the wind erosion erosivity of the region to reveal the spatial and temporal dynamics of its climate erosivity and conduct the abrupt change test; 3) Revealing the characteristics of graded geographical zoning of wind erosion climate erosivity in this region and the features of its variation and transfer. The study aims to provide a reference for preventing and controlling wind erosion in the arid desert region of northwestern China and support the construction of ecological security barriers in this region.

2 Research methods

2.1 Study area overview

The northwest arid desert region is located in the hinterland of Eurasia in mid-latitudes. This region covers most parts of Xinjiang, western Inner Mongolia, northwestern Qinghai and Ningxia, and the vast area of Hexi Corridor in Gansu, China. A geographical distribution pattern with the Tarim Basin in the west, the Helan Mountains in the east, the Altai Mountains in the north, and the Kunlun Mountains in the south has been formed here (Zulkar et al., 2021), with the coordinates of 34°27′18″‒49°04′43″N, 73°36′00″‒104°19′48″E. The geomorphological features of the study area are complex and diverse. Several zones with a “mountain-basin” interspersed or oasis-desert interlaced landform are distributed in this vast area. The climate in this region is dry, with 2500‒3500 hours of daylight all year round. The rainy season coincides with the hot season, with rainfall generally concentrated in July, August, and September. The average precipitation amount over multiple years is mostly 200 mm, with an overall geographical distribution pattern of more precipitation in the east and less in the west (Qian et al., 2011). The annual average wind speed is 2.51 m s‒1 (Liu, 2021), with the northwest wind being the dominant wind. The vegetation species are single with low coverage. There is primarily drought-resistant vegetation that is sparsely distributed. The vegetation includes Haloxylon ammodendron, Calligonum gobicum, Tamarix ramosissima, and Populus euphratica. The soil types are primarily sand in desert areas and sandy loam in oasis areas. The meteorological conditions of intense evaporation, drought, less precipitation, and gusty winds result in the strong wind erosion erosivity in this region, providing the necessary dynamic conditions for the occurrence of wind-drifted sand activities. The loose and poorly agglomerated soil texture offers a solid basis for desertification in this region. The sparse and low vegetation with poor species diversity has a limited capacity for protecting the ground surface, resulting in most zones in this region being exposed or semi-exposed for a long time. It has dramatically facilitated the wind erosion of ground-surface soil and wind- drifted sand activities.
Fig. 1 Geographical distribution of the northwest arid desert region

2.2 Data source

The meteorological data used in this study come from such indicators as the temperature, precipitation amount, relative humidity, and wind speed in the “China meteorological forcing dataset (1979‒2018)” (Yang and He, 2019) provided by the National Tibetan Plateau Data Center. Considering the lowest resolution of all data, this study has uniformly processed all data into raster data with a 0.1° resolution to ease statistical analysis. In this paper, one year is divided into four seasons per the division of meteorological seasons (Wang, 2019). That is, the spring is from March to May, summer is from June to August, autumn is from September to November, and winter is from December to February of the following year. For the convenience of description, the location of the hinterland distribution of the northwest arid desert region is specified in this paper as part of the combined area of southern and northern Xinjiang in the east part of Xinjiang and its nearby zones. There is a selection principle that the selected zones should be at, or around the geometric center of this region, with uneven changes of meteorological elements and concentrated distribution of high wind erosion erosivity values. Refer to the marked zones in Fig. 1 for the geographical coordinate range: 39°53′59″‒44°54′05″N, 89°25′14″‒93°23′52″E.

2.3 Data processing

2.3.1 Calculation of wind erosion climate erosivity factor

Through the FAO assessment method (Yue et al., 2022), the C value can be calculated with the formula as follows:
$C=\frac{1}{100}\sum\limits_{i=1}^{12}{{{{\bar{\mu }}}_{2}}^{3}}\times \left( 1-\frac{{{P}_{i}}}{ET{{P}_{i}}} \right)\times d$
In formula (1), C represents the wind erosion climate erosivity. ${{\bar{\mu }}_{2}}$represents the monthly average wind speed at the height of 2 m (unit: m s‒1). Pi represents the precipitation amount in the i month (unit: mm). ETPi represents the potential evapotranspiration amount in the i month (unit: mm). d represents the number of days in the i month.
In the original data set, the wind speed data were obtained at the height of 10 m. So, these data should be converted with the following formula (Liu et al., 2019).
${{u}_{2}}={{u}_{10}}\times \frac{4.87}{\ln (67.8\times 10-5.42)}$
In formula (2), ${{u}_{10}}$ represents the wind speed at the height of 10 m and ${{u}_{2}}$ represents the converted wind speed at the height of 2 m (unit: m s‒1).
In order to calculate the potential evapotranspiration amount, the method provided in “Guidelines on delimitation of ecological protection red line” (Environment Office Ecology [2017] No.48) was applied with the formula as follows (Lei et al., 2023):
$ET{{P}_{i}}=0.19\times {{(20+{{T}_{i}})}^{2}}\times (1-{{r}_{i}})$
In formula (3), ETPi represents the potential evapotranspiration amount in the i month (unit: mm), Ti represents the monthly average temperature (unit: ℃), and ri represents the monthly relative humidity (unit: %).

2.3.2 Mann-Kendall non-parametric abrupt change test method

The Mann-Kendall non-parametric abrupt test (Ma et al., 2021) is a method that can be used for climate diagnosis and prediction to judge whether there exists a phenomenon of abrupt climate change in a long time series and, if yes, the time when the abrupt change occurs. In this study, the test significance level α is set at 0.05. Then, if the statistic variable is ±1.96, 95% of the confidence interval is between ±1.96. If UF > 0, an upward trend can be predicted. If UF < 0, then a downward trend can be predicted.

2.4 Data visualization method

Use Excel-2019 tool to preprocess the obtained data, and combine python and Arcpy for data batch processing and statistics, and use software ArcGIS and Adobe-Illustrator to draw data visualization graphics.

3 Results and analysis

3.1 Characteristics of regional meteorological elements

Figure 2 shows the distribution of multi-year average wind speed in the northwest arid desert region. Figure 3 shows the trend analysis of wind factor changes. The inter-decades average wind speed in the region varies from 1.44 m s‒1 to 1.79 m s‒1. Its geographical distribution presents a relatively high wind speed pattern concentrated in the central and western areas. With the change in time series, there is an apparent change in the locations of the areas where the characteristics as mentioned above are displayed. The areas with an average wind speed of no less than 4 m s‒1 during the periods of 1979‒1988 (Fig. 2a) and 1989‒1998 (Fig. 2b) are primarily distributed in the northeast edge of the region with a pattern of “point shape”. However, it can be seen that areas with an average wind speed of no less than 4 m s‒1 during 1999‒2008 (Fig. 2c) and 2009‒2018 (Fig. 2d) appear in the hinterland of the region.
Fig. 2 Multi-year average wind speed distribution in the study area
Fig. 3 Trend analysis of wind factor changes

Note: The inner circle to the outer circle in the order of 1979‒1988, 1989‒1998, 1999‒2008, 2009‒2018.

The average wind speed in some of these areas varies from 6 m s‒1 to 7.5 m s‒1, and the areas with increased average wind speed expand in some phases of the time series.
Figure 4 shows the distribution of multi-year average temperature in the northwest arid desert region. Figure 5 shows the trend analysis of temperature factor changes. It can be seen that most of the inter‒decade average temperature is within the range of ‒5℃ to 5℃. In the geographical distribution of the whole region, there forms an arc-shaped strip zone extending from the southwest high-temperature concentrated area to the west area. The temperature at the strip zone’s two ends is generally relatively high, and the temperature in its middle part is low. It is also found that the arc-shaped zone is the primary area in the region where temperature changes. The temperature on both sides of the region has no noticeable change, while the temperature in some areas remains stable for a long time. Through calculation, it is found that the regional multi- year average temperature increases at a rate of 0.34 ℃ (10 yr)‒1, and in some hinterland areas, its increase rate can reach 0.42 ℃ (10 yr)‒1.
Fig. 4 Multi-year average temperature distribution in the study area
Fig. 5 Trend analysis of temperature factor changes

Note: The inner circle to the outer circle in the order of 1979‒1988, 1989‒1998, 1999‒2008, 2009‒2018.

The characteristics of the spatial and temporal distribution of precipitation in the study area from 1979 to 2018 have been analyzed, with the results shown in Fig. 6, and Fig. 7 shows the trend analysis of precipitation factor changes. It shows that the inter-decades geospatial distribution of the average precipitation all presents a pattern that high precipitation and extremely high precipitation are concentrated in several “point” areas in the southeast, northwest, and southwest edges of the northwest arid desert region. Most of the region has a shortage of precipitation, with the multi-year average precipitation amounts of the hinterland and its peripheral zones during different periods all below 200 mm. In terms of time-series distribution, precipitation presents a trend of increase. Specifically, the increase of precipitation is concentrated in some zones in the marginal areas of the region, while in the hinterland, the precipitation presents a pattern of multi-point, irregular increase. However, the precipitation amounts of most zones in this region are below 200 mm. Precipitation from 1999 to 2008 (Fig. 6c) shows the most significant trend of increase, while the areas with increased precipitation from 2009 to 2018 (Fig. 6d) expand considerably.
Fig. 6 Multi-year average precipitation distribution in the study area
Fig. 7 Trend analysis of precipitation factor changes

Note: The inner circle to the outer circle in the order of 1979‒1988, 1989‒1998, 1999‒2008, 2009‒2018.

3.2 Spatial and temporal dynamics of regional wind erosion climate erosivity

3.2.1 Spatial distribution of wind erosion climate erosivity

Figure 8 shows the features of inter-decade variation of average wind erosion climate erosivity in the study area from 1979 to 2018.
Fig. 8 Inter‒decades spatial distribution of wind erosion climate erosivity
In general, the distribution of multi-year average C values in the northwest arid desert region shows an overall pattern of concentrated distribution of zones with high C values and a decreasing trend of C values from the hinterland of the arid desert region to the surrounding areas, respectively. Therefore, two low C values concentrated areas have formed along the northwest and south edges of the region. Meanwhile, the eastern areas with high wind erosion climate erosivity values have been distributed along the border with Mongolia for a long time.
In terms of time series, the spatial distribution of C values in the northwest arid desert region varied significantly from the 1970s to the 2010s. From 1979 to 1988, three areas with high C values of wind erosion climate erosivity were distributed in the hinterland and west of the region (Fig. 8a). The average wind erosion erosivity in most southwestern areas of the region varied from 0 to 50, with a scattered point‒shape distribution of areas with high erosivity values. From 1989 to 1998, two areas with high C values of wind erosion climate erosivity were distributed in the hinterland and east of the region (Fig. 8b). Compared with the areas during the period from 1979 to 1988, the areas with high erosivity values had decreased significantly, and the average wind erosion climate erosivity in the region had also shown a trend of decrease. From 1999 to 2008 (Fig. 8c) and 2009 to 2018 (Fig. 8d), the average C values in the region presented a pattern of overall decrease. However, the C values in a few areas had increased.
Meanwhile, the wind erosion climate erosivity distribution in the hinterland of the region showed a rapid increase in the potential risk of wind erosion, and a more concentrated distribution of areas with high C values, while the areas with high erosivity values expanded. The wind erosion erosivity in the southeastern part of the region ranged from 50 to 100. The southeastern areas with low erosivity values also expanded.

3.2.2 Seasonal variation trend of wind erosion climatic erosivity

Figure 9 shows the seasonal distribution features of wind erosion climate erosivity. The wind erosion climate erosivity in the arid desert region can be seen to present significant inter-month variation. The variation has a general characteristic: the highest erosivity occurs in spring and summer, the second highest erosivity occurs in winter, and the lowest erosivity occurs in autumn. Specifically, in the spring seasons of the four periods, the C values of climate erosivity that are over 20 all appeared in the hinterland and the western part of the region. The seasonal erosivity in most parts of the region ranged from 0 to 20.
Fig. 9 Characteristics of seasonal distribution of wind erosion climate erosivity
Meanwhile, with the change in time series, the wind erosion climate erosivity in spring presented an overall trend of decrease, while in some areas, it presented a pattern of increasing first and decreasing later. The change of wind erosion climate erosivity in summer presented an overall decrease trend. However, the peak value of erosivity increased at a rate of 4.1 (10 yr)‒1. The distribution of southeastern areas with high erosivity values changed from the previous relatively concentrated pattern to a pattern of scattered point-shaped distribution, while the change of the distribution areas with high values in the central and western areas was not prominent. Meanwhile, in the autumn and winter seasons, areas with C values lower than zero were distributed throughout the region, transferred from the previous concentrated distribution in the northeast part of the region. The phenomenon emerged that areas with high wind erosion erosivity values expanded during these seasons while the erosivity values changed irregularly in the same period.
In order to explore whether there is any abrupt change in wind erosion climate erosivity in the northwest arid desert region, and determine the time of abrupt change if any, the Mann-Kendall non-parametric abrupt change test method that is commonly used in climate diagnosis and prediction, is applied to judge whether the climate erosivity is in natural fluctuation to better measure and predict the trend. Figure 10 shows the region’s seasonal abrupt change test of wind erosion climate erosivity. It can be seen that the UF in most of the period from 1979 to 2018 is below zero, which indicates the wind erosion climate erosivity in the arid desert region is in a trend of long-term decrease. However, there were also short periods of increase, such as the spring, autumn, and winter during the 1980s and the winter during the first decade of this century. The periods with a significant downward trend appeared in the spring at the end of the last century and the beginning of this century, as well as in the autumn of the long time series from 1993 to 2016 and the winner of the period from 1990 to 2000. In terms of the time of abrupt changes, it is found that most abrupt changes occurred in spring and winter, with four time-points in each season. Meanwhile, there were three time-points of abrupt changes in summer, and in autumn, there was the least one time-point.
Fig. 10 Seasonal abrupt change test of wind erosion climate erosivity

Note: UF and UB are indicators of trend magnitude.

3.3 Graded geospatial distribution of wind erosion climate erosivity

Figure 11 shows the graded geospatial characteristics of wind erosion climate erosivity in the study area. It can be seen that the graded geographical space of the wind erosion climate erosivity in the arid desert region presents distinct differences.
In general, during the four periods of 1979‒1988, 1989‒1998, 1999‒2008 and 2009‒2018, the wind erosion degrees in the hinterland of the arid desert region were all higher than those in the peripheral areas. One or several closed areas with high soil erosion degrees formed during different periods. The scarce precipitation, high evaporation and temperature, relatively low relative humidity, and strong wind in these areas all contribute to the formation of these areas. Therefore, the manifestation of the strongest wind erosion climate erosivity with the highest level is the most eroded soil by wind. In the time series mentioned above, the overall variation of the wind erosion degree in the Xinjiang Uygur Autonomous Region presents a pattern of first increasing and then decreasing in the area with low erosion degree, with a pattern of first increasing and then decreasing in the area with moderate erosion degree. However, the area with high erosion degree increased slightly, which is related to the arid desert region’s hinterland primarily distributed in this area.
Fig. 11 Graded geospatial distribution of wind erosion climate erosivity in the study area
Meanwhile, the Xinjiang region is also the primary region where high wind erosion types are distributed in the study area, with an area coverage ratio of 2.21%‒2.26%. The Inner Mongolia Autonomous Region part within the geographical range of the northwest arid desert region has primarily low and moderate wind erosion degrees. However, during some time-series periods, the area of high wind erosion tends to increase there. The area of high wind erosion there is generally distributed along the border with Mongolia, with a trend of erosion degree gradually decreasing inland. During 1979‒1988, there were some concentrated distribution zones of moderate wind erosion in the northern area of the Qinghai Province part within the geographical range of the study area. In other time series, there was primarily slight erosion, with irregular and sporadic point- shape distribution of moderately and severely eroded zones and irregular changes in distribution areas. The distribution of wind erosion degrees along the Hexi Corridor in Gansu Province presents a diversified pattern. Moderate and severe wind erosion is primarily distributed in its northwestern part bordering Xinjiang and its northern part bordering Inner Mongolia. There is primarily slight erosion in other areas, with a sporadic distribution of moderately wind-eroded areas. The Ningxia Hui Autonomous Region part within the geographical range of the northwest arid desert region has primarily slight and moderate wind- erosion degrees. The time when the severely wind-eroded area occurred is irregular, while its location and size are relatively fixed. In this part of the region, the area severely eroded by wind is generally distributed on its northwest edge.

3.4 Spatial and temporal transfer and variation characteristics of wind erosion climate erosivity

The transfer and variation characteristics of wind erosion climate erosivity in the northwest arid desert region have been analyzed, as shown in Fig. 12. The study shows that the geospatial distribution of wind erosion climate erosivity’s transfer and variation in the region is uneven, presenting significant differences. In general, the wind erosion climate erosivity’s variation in the geographical range of the study area during 1979‒1988 is characterized by some areas with a medium and high increase of climate erosivity primarily concentrated in eastern Xinjiang, where the southern Xinjiang adjoins northern Xinjiang geographically. In addition, some zones with an apparent increase of erosivity are also concentratedly distributed in the combination area of northeastern Gansu and western Inner Mongolia. Meanwhile, other zones with increased wind erosion climate erosivity are distributed irregularly with a scattered “point- shaped” or “striped” pattern. The areas with decreased wind erosion climate erosivity are primarily distributed in the northwestern Gansu and Xinjiang bordering areas and the adjacent areas of northern Qinghai and Xinjiang. In addition, some areas with decreased climate erosivity are concentrated in the east part of the arid desert region and some western parts of Xinjiang. Generally speaking, the transfer and variation characteristics of wind erosion climate erosivity in the region are complex and diverse, with various geographical distribution patterns. Meanwhile, the climate erosivity presents an overall trend of slightly decreasing, with some areas witnessing an increase or a significant increasing trend of the erosivity.
Fig. 12 Characteristics of spatial and temporal transfer and variation of wind erosion climate erosivity in the study area

4 Discussion

The wind erosion intensity is primarily affected by climate conditions as a driving factor. However, the ecosystem in the northwest arid desert region is susceptible to changes in the meteorological elements because of the abnormal changes in atmospheric circulation and abrupt changes in the climate in the large-scale natural weather zone area. In addition, the climate conditions of aridity, less rainfall, and intense evaporation, plus a fragile ecosystem in the study area, have jointly contributed to the formation of China’s most primary wind erosion landforms in this region. Studying the spatial and temporal variation of wind erosion climate erosivity and its response to climate variability in this region can help evaluate the potential occurrence risk of soil wind erosion.

4.1 Analysis of study methods and results’ feasibility

Using the calculation formula of wind erosion climate erosivity commonly adopted in the industry, this study has explored the potential occurrence risk of soil wind erosion and its transfer and variation features in the arid desert region, combining quantitative and qualitative methods. However, unlike similar studies that adopted the meteorological data from positioning monitoring stations, this study used the meteorological element data coming from the “China meteorological forcing dataset” (Yang et al., 2010; He et al., 2020).
This dataset avoided the risk of missing meteorological element data whose time differs from when the monitoring station was constructed in the long time series or discontinuous data caused by various factors. It can ensure that the calculation and analysis can be carried out directly on the basis of the original data obtained and that human manipulation caused by the shortage of measurement data in the process can be reduced, thus effectively minimizing study errors. Mature study methods and sufficient original research data generate scientific and reliable results. Furthermore, on the basis of the C values’ calculation, the methods of erosion grading and erosivity spatial and temporal transfer and variation matrix are applied in this study. These methods have provided theoretical support for innovative research on the spatial and temporal variation of wind erosion erosivity in large-scale natural meteorological areas.

4.2 Spatial and temporal variation characteristics of meteorological elements

In fact, scholars in the industry have paid wide attention to the relationship between meteorological elements (Qi et al., 2015) and wind erosion erosivity. Relevant research shows a high correlation between regional meteorological elements and the factor index of wind erosion erosivity. In the study on the influence of climate conditions on the wind erosion erosivity in Xinjiang (Wang et al., 2022b), it is found that the meteorological elements that influence the C value are wind speed, temperature, precipitation amount, and relative humidity in descending order of influence degree. In terms of geographical distribution, the elements of precipitation amount and relative humidity significantly influence northern Xinjiang. Meanwhile, wind speed plays a primary role in affecting wind erosion erosivity in some eastern and southern Xinjiang regions. When studying the wind erosion climate erosivity in southern Africa, some scholars (Zhao et al., 2021) have found that the decrease of wind speed near the ground surface can lead to a 39.89% decrease in soil wind erosion in the study area. They also found that the influencing degrees of precipitation amount and temperature vary from 18.96% to 24.63%. In studying the driving factors of wind erosion erosivity in Qinghai Province, some researchers (Wu et al., 2018) have found that precipitation amount is the primary factor that influences the C value of the Qaidam Basin, while wind speed and average temperature are the primary factors that influence the C values of the east Kunlun Mountains and west part of the source region of the Yangtze River and Yellow River. When studying the response degrees of wind erosion erosivity to changes in meteorological elements in north China, some scholars (Yang and Lu, 2016) found that a 1% change in wind speed will lead to a change of more than 3% in C value. They also found that the impacts of precipitation amount and relative humidity on wind erosion erosivity are smaller than wind speed, with the C value not sensitive to changes in average temperature. The distribution of regional wind erosion climate erosivity can be found to present considerable zonality and variability. In the context of large-scale geographical space, the distribution of meteorological elements in the northwest arid desert region also differs substantially from the distribution in other regions.
The wind is the essential driving factor in the genesis and development of soil and can directly affect soil erosion intensity. The investigated multi-year average wind speed in the northwest arid desert region increases significantly in the hinterland, with the areas affected by high wind speed increasing simultaneously. The geographical distribution of the average wind speed presents a concentrated distribution of relatively high wind speeds in this region’s central and western parts. The average wind speed in the hinterland can reach 6 to 7.5 m s‒1, and the study area’s relatively high wind speed condition is a strong driving force for the occurrence of soil wind erosion in the region. Research has revealed that when the temperature rises, air humidity decreases, and near ground‒surface evaporation increases, resulting in the increase of wind erosion risk of exposed and semi-exposed soil in the region in question. Against the backdrop of global warming, this study found that the multi-year average temperature in the northwest arid desert region increases at a rate of 0.34 ℃ (10 yr)‒1, with that temperature in some areas of its hinterland reaching as high as 0.42 ℃ (10 yr)‒1. It indicates that the environment of the study area is in a state of warming at a relatively high rate, which is consistent with the results of previous studies (Liu et al., 2020). Meanwhile, the geographical distribution of average temperature throughout this region presents a pattern that the temperature variation in the hinterland is more complex than that of its surrounding areas. It shows that areas with high average temperatures also appear at the edge of the region. However, these areas are primarily concentrated in the region likely to be eroded by wind. The overall increase in temperature makes soil wind erosion more likely to occur.
The study also found that the precipitation in the arid desert region presents an overall trend of increase. Specifically, areas with increased precipitation in individual marginal zones of the region cluster together. In the hinterland, precipitation increases at multiple area spots, with the amount still lower than 200 mm. Meanwhile, the areas with high precipitation primarily appear in this region’s marginal zones. Some research (Yuan et al., 2022) has proved that increased precipitation can significantly reduce the likeliness of soil wind erosion. However, soil wind erosion results from the multi factors’ comprehensive effect. It can not sufficiently reveal the response of wind erosion climate erosivity to changes in meteorological elements in a quantitative way by only considering the response mechanism of wind erosion to a single meteorological element. Therefore, this study needs to use the wind erosion climate erosivity formula to analyze and judge the relevant pattern of wind erosion occurrence in this region in a comprehensive way.

4.3 Analysis on the causes of climatic erosivity change of wind erosion

On the basis of the FAO formula, this study found that the average C values in this region decrease as a whole, which is consistent with the results of previous studies (Qi et al., 2019; Ma et al., 2021; Wang et al., 2021b) that used a single administrative region as their study objects. However, the average C values in a few areas, such as the hinterland, have increased. Furthermore, the wind erosion climate erosivity in the hinterland presents a pattern of increasing potential occurrence risk of soil wind erosion and increasing areas with high erosivity values. In most other areas, the wind erosion erosivity falls into a range of 0 to 100, consistent with the previous studies (Dong et al., 1994). However, due to the differences in time series and data sources, there are differences in distribution areas. In addition, the areas with low values also expand significantly. The seasonal variation trend of wind erosion climate erosivity has been investigated. The results show that the factor index of wind erosion climate erosivity in the arid desert region presents substantial inter‒month variation. The general characteristic is that the factor index of wind erosion climate erosivity is decreasing for a long time, with the most significant decrease in spring and summer, the second largest decrease in winter, and the slightest decrease in autumn. This finding differs from the results of some studies that used specific regions, such as the western Hexi Corridor and the north wind erosion areas, as their research objects (Niu et al., 2017; Han, 2019). The abrupt changes in wind erosion climate erosivity in the region and their occurrence time have been investigated. The results show that in spring there occur the most abrupt change points.
Meanwhile, when grading the geographical distribution of wind erosion climate erosivity in the region, the researchers of this study found that the erosion degrees in the hinterland of the desert region at all four stages are higher than those in the surrounding areas. One or several closed areas with high soil erosion degrees are formed at different stages. These areas are primarily distributed in the east part of Xinjiang, where southern Xinjiang adjoins northern Xinjiang geographically. This finding is consistent with the results of previous studies (Wang et al., 2021b). In addition, because most parts of Xinjiang are located in the arid desert region, its overall soil erosion intensity is higher than that of other areas. Thus, Xinjiang is also the study area's primary distribution area of high wind erosion types. The analysis of the transfer and variation matrix of wind erosion climate erosivity in the region shows that the transfer and variation features of climate erosivity are complex and diverse, with various forms of geographical distribution patterns. Meanwhile, the transfer and variation of the climate erosivity present an overall trend of a slight decrease in small areas. In some areas, they increase or present a significant increasing trend.

4.4 Limitations of data and methods

First, the data used in this study come from meteorological observation data, re-analyzed data, and satellite remote sensing data with values without physical significance being removed. Although it secures the continuity of long-time series data and the integrity of meteorological element data, the accuracy of original data has been compromised to some extent during the statistics process. Combining the continuous driving factor data and monitoring stations’ high-accuracy observation data could yield more accurate calculation results. Further research should be carried out in the direction just described. Second, the methods applied in this study can only use the meteorological data to assess the climate erosivity in the region. These methods can not provide a clear and comprehensive evaluation of the potential occurrence risk of soil wind erosion under the influence of climate erosivity in the study area by combing the differences of ground-surface elements. Thus, further research should emphasize the wind erosion assessment methods that combine the comprehensive effects of multiple factors, such as the ground-surface elements, with wind erosion erosivity as their basis.

5 Conclusions

On the basis of the geospatial distribution of meteorological elements, spatial and temporal dynamic distribution of climate erosivity, characteristics of graded geographical zoning of climate erosivity, and corresponding transfer features of wind erosion climate erosivity in the study area, the variation characteristics of wind erosion climate erosivity in the northwest arid desert region during the period of 1979‒2018 have been analyzed in this study, with the primary conclusions as shown below:
(1) Among the meteorological elements in the study area, precipitation has a relatively concentrated geospatial distribution and presents a trend of increase. The precipitation at the beginning of this century shows the most significant trend of increase. The areas with increased precipitation in the first decade of this century expanded considerably. Meanwhile, the region’s temperature and wind speed during the same period gradually increased, and the areas affected by high wind speed also expanded.
(2) The wind erosion climate erosivity in the northwest arid desert region shows an overall decrease trend. However, the climate erosivity in a few areas increases, with the wind erosion climate erosivity in the hinterland presenting a trend of increase. Meanwhile, the areas with high erosivity values increase. The values of wind erosion erosivity in most other areas fall into a range of 0‒100, and the areas with low erosivity values also expand significantly. In addition, the monthly variation of wind erosion climate erosivity varies significantly. It exhibits a general characteristic that the most significant variation appears in spring and summer, the second greatest variation in winter, and the slightest variation in autumn.
(3) At all four stages, the wind erosion intensity in the hinterland of the arid desert region is more robust than that of its surrounding areas. During different stages, there form one or several closed annular areas with high soil erosion degrees. The east part of Xinjiang is a primary distribution area of high wind erosion types in the study area.
(4) The transfer and variation features of wind erosion climate erosivity in the region are complex and diverse, with their geographical distribution presenting various pattern forms. The transfer and variation of climate erosivity in the region decrease slightly as a whole, while in some areas, they increase or present a trend of high increase. The areas with a moderate or high increase of erovisity are primarily distributed in the east part of Xinjiang, where southern Xinjiang adjoins northern Xinjiang geographically.

Acknowledgements

The datasets is provided by National Tibetan Plateau Data Center (http://data.tpdc.ac.cn). We thank our colleagues for their help with the experiments.

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]
Chen S X, Dong Y X. 2020. A review of the research on wind erosion climatic erosivity. Journal of desert Research, 40(5): 65-73. (in Chinese)

DOI

[2]
Chen T, Zou L, Xia J, et al. 2022. Decomposing the impacts of climate change and human activities on runoff changes in the Yangtze River Basin: Insights from regional differences and spatial correlations of multiple factors. Journal of Hydrology, 615: 128649. DOI: 10.1016/j.jhydrol.2022.128649.

DOI

[3]
Chepil W S, Milne R A. 1939. Comparative study of soil drifting in the field and in a wind tunnel. Scientific Agriculture, 19: 249-257.

[4]
Chepil W S, Siddoway F H, Armbrust D V, et al. 1962. Climatic factor for estimating wind erodibility of farm fields. Journal of Soil and Water Conservation, 17(4): 162-165.

[5]
Dang X H, Pan X, Gao Y, et al. 2019. Spatial heterogeneity of wind-eroded soil particles around Nitraria tangutorum nebkhas in the Ulan Buh Desert. Écoscience, 26(4): 347-358.

DOI

[6]
Dong Y X, Kang G D. 1994. Study on the wind erosion climate erosivity in arid and semi-arid areas in China. Journal of Soil and Water Conservation, 8(3): 1-7. (in Chinese)

[7]
Han L. 2019. Temporal and spatial variation characteristics of wind speed and its influence on wind erosion climatic erosivity in the wind erosion region of northern China. Diss., Yantai, China: Ludong University.

[8]
He J, Yang K, Tang W J, et al. 2020. The first high-resolution meteorological forcing dataset for land process studies over China. Scientific Data, 7(1): 25. DOI: 10.1038/s41597-020-0369-y.

DOI PMID

[9]
Hu S L, Yu B, Luo S, et al. 2022. Spatial pattern of the effects of human activities on the land surface of China and their spatial relationship with the natural environment. Environment, Development and Sustainability, 24(8): 10379-10401.

DOI

[10]
Lei Y N, Li M, Cheng L. 2023. Spatio-temporal characteristics of rainfall erosivity and wind erosion climatic erosivity in Shaanxi Province. Research of Soil and Water Conservation, 30(3): 47-54, 61. (in Chinese)

[11]
Li D J, Xu D Y, Ding X, et al. 2018. Changes of wind erosion climatic erosivity and vegetation dynamics response in northern China from 1981 to 2010. Research of Soil and Water Conservation, 25(2): 15-20. (in Chinese)

[12]
Liu H, Li X Y, Xiao J H, et al. 2019. Variations of wind erosion climatic erosivity in the Yarlung Zangbo River Basin during 1961-2015. Scientia Geographica Sinica, 39(4): 688-695. (in Chinese)

DOI

[13]
Liu K, Nie G G, Zhang S. 2020. Study on the spatiotemporal evolution of temperature and precipitation in China from 1951 to 2018. Advances in Earth Science, 35(11): 1113-1126. (in Chinese)

DOI

[14]
Liu Y. 2021. Temporal and spatial variation characteristics and influencing factors of actual evapotranspiration in arid region of northwest China. Diss., Urumqi, China: Xinjiang University. (in Chinese)

[15]
Liu Y H, Gao G, Li H M, et al. 2022. Spatiotemporal variations and causes of wind/rainfall erosion climatic erosivity in Qinghai Province, China. Atmosphere, 13(10): 1649. DOI: 10.3390/atmos13101649.

DOI

[16]
Lou J P, Wang X M, Cai D W. 2019. Spatial and temporal variation of wind erosion climatic erosivity and its response to ENSO in the otindag desert, China. Atmosphere, 10(10): 614. DOI: 10.3390/atmos10100614.

DOI

[17]
Ma X X, Xiao J H, Yao Z Y et al. 2021. Spatio-temporal evolution of wind erosion climatic erosivity in the Alxa Plateau during 1960-2017. Scientia Geographica Sinica, 41(6): 1096-1104. (in Chinese)

DOI

[18]
Merrill S D, Black A L, Fryrear D W, et al. 1999. Soil wind erosion hazard of spring wheat-fallow as affected by long-term climate and tillage. Soil Science Society of America Journal, 63(6): 1768-1777.

DOI

[19]
Niu Q H, Qu J J, An Z S. 2017. Characteristics of wind erosion climate erosivity in Dunhuang Yadan Geo-Park of Gansu Province. Journal of Desert Research, 37(6): 1066-1070. (in Chinese)

[20]
Qi D L, Han T F, Zhao Q M, et al. 2019. Characteristics of regional variation of wind erosion climate erosivity and number of wind days in winter and spring in Qinghai Province. Soil and Water Conservation Research, 26(2): 23-30, 36. (in Chinese)

[21]
Qi D L, Li X D, Su W J, et al. 2015. Tendency of spatiotemporal evolution of wind erosion climatic erosivity in Qinghai Province in recent 50 years. Research of Soil and Water Conservation, 22(6): 234-239. (in Chinese)

[22]
Qian Z A, Song M H, Li W Y, et al. 2011. Global, China-Mongolia arid and semi-arid areas (CMASA) and the details of precipitation distribution in part regions of CMASA. Plateau Meteorology, 30(1): 1-12. (in Chinese)

[23]
Skidmore E L. 1986. Wind erosion climatic erosivity. Climatic Change, 9(1): 195-208.

DOI

[24]
Wang H F, Zhang R, Cai Y, et al. 2022a. Ecological uniqueness and the determinants in arid desert ecosystems of northwest China. Global Ecology and Conservation, 34: e02005. DOI: 10.1016/j.gecco.2022.e02005.

DOI

[25]
Wang S M, Liu Q H, Huang C. 2021a. Vegetation change and its response to climate extremes in the arid region of northwest China. Remote Sensing, 13(7): 1230. DOI: 10.3390/rs13071230.

DOI

[26]
Wang Y, Zhao J, Cheng Y C. 2005. Analysis of wind erosion climatic erosivity at agri-pasture transition zone in north area of Yinshan Mountain. Acta Agriculturae Boreali-Sinica, 20(S1): 57-60. (in Chinese)

DOI

[27]
Wang Y Q, Fan W B, Xu Z Y, et al. 2021b. Spatiotemporal variation characteristics of wind erosion climate in Xinjiang in recent 50 years. Research of Soil and Water Conservation, 28(4): 22-28. (in Chinese)

[28]
Wang Y Q, Yang H M, Fan W B, et al. 2022b. Migration characteristics of wind erosion climate erosivity and its influencing factors in Xinjiang in recent 50 years. Arid Land Geography, 45(2): 370-378. (in Chinese)

[29]
Wang Z. 2019. Study on the seasonal division of China and its prediction of summer precipitation. Diss., Lanzhou, China: Lanzhou University. (in Chinese)

[30]
Wu C Y, Chen K L, Cao G C, et al. 2018. The spatial and temporal differences and driving forces of wind erosion climatic erosivity in Qinghai Province from 1984 to 2013. Geographical Research, 37(4): 717-730. (in Chinese)

DOI

[31]
Xie J L, Lu Z X, Xiao S C, et al. 2021. Driving force and ecosystem service values estimation in the extreme arid region from 1975 to 2015: A case study of Alxa League, China. Chinese Geographical Science, 31(6): 1097-1107.

DOI

[32]
Yang F B, Lu C H. 2016. Assessing changes in wind erosion climatic erosivity in China’s dryland region during 1961-2012. Journal of Geographical Sciences, 26(9): 1263-1276.

DOI

[33]
Yang K, He J. 2019. China meteorological forcing dataset (1979-2018). National Tibetan Plateau/Third Pole Environment Data Center. DOI: 10.11888/AtmosphericPhysics.tpe.249369.file.

DOI

[34]
Yang K, He J, Tang W J, et al, 2010. On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetan Plateau. Agricultural and Forest Meteorology, 150(1): 38-46.

DOI

[35]
Yuan L M, Yang Z G, Xue B, et al. 2022. Heterogeneity of soil moisture of blowouts in Hulunbuir grassland. Arid Zone Research, 39(5): 1598-1606. (in Chinese)

[36]
Yue S P, Yan Y C, Zhang S W, et al. 2022. Changes in climate factors and their impacts on wind erosion climatic erosivity in farming-pastoral zone of northern China. Chinese Geographical Science, 32(4): 665-675.

DOI

[37]
Zhao C N, Zhang H B, Wang N, et al. 2021. Impacts of climate change on wind erosion in southern Africa between 1991 and 2015. Land Degradation & Development, 32(6): 2169-2182.

DOI

[38]
Zhang Y X, LI P, Xu G C, et al. 2023. Temporal and spatial variation characteristics of extreme precipitation on the Loess Plateau of China facing the precipitation process. Journal of Arid Land, 15(4): 439-459.

DOI

[39]
Zou C X, Shen X D, Li X Z, et al. 2011. Characteristics of wind erosion climatic erosivity in agro-pastoral ecotone of north Yin Mountain, Inner Mongolia, China. Journal of Jilin University (Earth Science Edition), 41(4): 1172-1178. (in Chinese)

[40]
Zulkar H L, Zhao T N, Jiang Q O. 2021. Boundary scope and change of arid desert area in northwest China. Arid land Geography, 44(6): 1635-1643. (in Chinese)

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