Spatiotemporal variation and driving factors of soil wind erosion in the arid and semi-arid areas of northern China in 2001-2020

doi:10.7522/j.issn.1000-694X.2025.00149

Journal of Desert Research ›› 2026, Vol. 46 ›› Issue (2): 164-176.DOI: 10.7522/j.issn.1000-694X.2025.00149

Spatiotemporal variation and driving factors of soil wind erosion in the arid and semi-arid areas of northern China in 2001-2020

Shiyu Wang(), Xuesong Wang()

State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction / MOE Engineering Research Center of Desertification and Blown-Sand Control / Faculty of Geographical Science，Beijing Normal University，Beijing 100875，China

Received:2025-07-24 Revised:2025-09-08 Online:2026-03-20 Published:2026-04-13
Contact: Xuesong Wang

Abstract

Abstract:

The arid and semi-arid areas of northern China have complex and diverse topography and fragile ecological environment. Soil wind erosion is a key factor affecting the stability of the ecosystem and social and economic development in the areas. This study uses the Revised Wind Erosion Equation （RWEQ） to quantitatively analyze the spatial distribution and temporal dynamics of soil wind erosion in the study area from 2001 to 2020， and combined with geographic detector to further explore the driving factors of soil wind erosion. The results indicate that：（1） During the study period， the multi-year average actual soil wind erosion modulus of the study areas is 13 449.59 t·km^-2·a^-1， which was dominated by severe erosion and mainly distributed in the center of the Tarim Basin and the central and western parts of the Inner Mongolia Plateau. The actual soil wind erosion modulus shows a fluctuating downward trend， which decreases at a rate of 102.78 t·km^-2 per year. （2） During the study period， there are significant differences in the actual soil wind erosion modulus of different land use types in the study area. Whether it was the land use type that has been converted or the land use type that has not been converted， the order of the actual soil wind erosion modulus in 2020 was： sandy land > grassland > cultivated land > construction land > forestland. In addition， the actual soil wind erosion modulus of the newly-added grassland and newly-added cultivated land in the arid and semi-arid areas of northern China is relatively high， which were 13 695.88 t·km^-2·a^-1 and 7 933.25 t·km^-2·a^-1 respectively， and were higher than the actual soil wind erosion modulus of the grassland and cultivated land that did not change during the study period， which were 19.90% and 58.53% respectively. （3） Among the many factors affecting the soil wind erosion in the study areas， the weather factor was the dominant factor （q=0.312， P<0.01）. Among them， the wind factor and the actual soil wind erosion modulus show a relatively significant positive correlation of moderate intensity （r=0.43， P<0.05）.

Key words: the arid and semi-arid areas of northern China, RWEQ, geographic detector

CLC Number:

S155.1

Shiyu Wang, Xuesong Wang. Spatiotemporal variation and driving factors of soil wind erosion in the arid and semi-arid areas of northern China in 2001-2020[J]. Journal of Desert Research, 2026, 46(2): 164-176.

Figures/Tables 10

Fig.1 Geographical location in the arid and semi-arid areas of northern China （ASANC）

Table 1 Model input parameters and data description

模型名称	输入数据	参数	时间尺度	时间分辨率	空间分辨率	数据网址
RWEQ	气象数据	风速	2001—2020年	逐时	0.5°×0.625°	https://disc.gsfc.nasa.gov
		降水	2001—2020年	逐时	0.5°×0.625°	https://disc.gsfc.nasa.gov
		雪深	2001—2020年	逐时	0.5°×0.625°	https://disc.gsfc.nasa.gov
		潜在蒸散发	2001—2020年	逐月	1 km×1 km	https://www.tpdc.ac.cn
	土壤数据	土壤质地	不变量	不变量	1 km×1 km	https://www.ncdc.ac.cn
	地形数据	DEM	不变量	不变量	250 m×250 m	https://www.resdc.cn
	植被数据	NDVI	2001—2020年	逐月	1 km×1 km	https://www.resdc.cn
	土地利用	CLCD	2001—2020年	逐年	30 m×30 m	https://www.ncdc.ac.cn

Table 2 Types of interaction between two covariates［50］

交互类型	判定依据
非线性减弱	$q (X 1 ⋂ X 2) < M i n (q (X 1), q (X 2))$
单因子非线性减弱	$M i n (q (X 1), q (X 2)) < q (X 1 ⋂ X 2) < M a x (q (X 1), q (X 2))$
双因子增强	$q (X 1 ⋂ X 2) > M a x (q (X 1), q (X 2))$
独立	$q (X 1 ⋂ X 2) = q (X 1) + q (X 2)$
非线性增强	$q (X 1 ⋂ X 2) > q (X 1) + q (X 2)$

Table 2 Types of interaction between two covariates［50］

交互类型	判定依据
非线性减弱	$q (X 1 ⋂ X 2) < M i n (q (X 1), q (X 2))$
单因子非线性减弱	$M i n (q (X 1), q (X 2)) < q (X 1 ⋂ X 2) < M a x (q (X 1), q (X 2))$
双因子增强	$q (X 1 ⋂ X 2) > M a x (q (X 1), q (X 2))$
独立	$q (X 1 ⋂ X 2) = q (X 1) + q (X 2)$
非线性增强	$q (X 1 ⋂ X 2) > q (X 1) + q (X 2)$

Fig.2 Spatial distribution of multi-year average actual soil wind erosion modulus in the ASANC from 2001 to 2020

Fig.3 Spatiotemporal dynamics of actual soil wind erosion modulus in the ASANC from 2001 to 2020

Fig.4 Landuse transfer chord diagram in the ASANC from 2001 to 2020

Fig.5 The actual soil wind erosion modulus of different landuse in the ASANC in 2001 and 2020

Fig.6 Factor detection of the actual soil wind erosion modulus in the ASANC from 2001 to 2020

Fig.7 Interaction detection of the actual soil wind erosion modulus in the ASANC from 2001 to 2020

Table 3 Comparison results of RWEQ with measurement［55-56］

研究区域	研究时段	研究方法	纬度	经度	原文结果 /(t·km^-2·a^-1)	本文结果 /(t·km^-2·a^-1)
新疆准东地区	2015年	¹³⁷Cs示踪法	44°16′14″N	90°21′00″E	2 644.08	3 678.03
			45°06′37″N	88°35′20″E	3 855.57	5 266.36
			44°29′58″N	89°54′54″E	1 871.13	4 340.87
			44°47′12″N	89°21′06″E	1 840.09	1 197.04
	2016年	粒度对比法	44°06′34″N	90°00′55″E	2 585.58	2 842.68
	2016年	粒度对比法	45°00′05″N	89°14′04″E	2 857.28	2 199.54

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Spatiotemporal variation and driving factors of soil wind erosion in the arid and semi-arid areas of northern China in 2001-2020

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