1.State Key Laboratory of Soil and Water Conservation and Desertification Control,College of Soil and;Water Conservation Science and Engineering,Northwest A&F University,Yangling,Shaanxi 712100,China
2.Institute of;Soil and Water Conservation,Chinese Academy of Sciences and Ministry of Water Resources,Yangling,Shaanxi 712100,China
Objective The impacts of dynamic changes in different land use types on water-induced soil erosion in the Xinjiang Uygur Autonomous Region from 2003 to 2023 were investigated in order to provide a scientific basis for the scientific and rational formulation of soil and water conservation measures and the optimization of regional territorial spatial patterns. Methods Taking the Xinjiang Uygur Autonomous Region as the research object, the revised universal soil loss equation (RUSLE) model and the land use transfer matrix method were used to systematically analyze the spatiotemporal evolution of land use patterns and the variation characteristics of soil erosion intensity from 2003 to 2023 in this region, and to explore the correlation mechanism between the two factors. Results ① From 2003 to 2023, bare land and grassland were the dominant land use types in Xinjiang, with their combined proportion remaining above 90% and showing a shrinking trend. Cultivated land and construction land expanded significantly, with their area proportions increasing from 3.87% to 5.40% and from 0.10% to 0.33%, respectively. Forest land area increased steadily, while water area increasing first and then decreased. Land use conversion mainly occurred between bare land and grassland. ② The multi-year average water-induced soil erosion modulus in Xinjiang from 2003 to 2023 was 282.24 t/(km²·a), and the erosion intensity showed a trend of first fluctuating and then decreasing. The area of slight erosion increased to 95.63%, and moderate and above-intensity erosion approached zero by 2023.③ Land use change in Xinjiang from 2003 to 2023 had a significant regulatory effect on water-induced soil erosion. The increase in water areas, forest land, and wetlands effectively inhibited erosion intensity, while the expansion of construction land and cultivated land led to an increase in the area of slight and light erosion. Conclusion Water-induced soil erosion in Xinjiang from 2003 to 2023 was dominated by slight erosion, followed by light erosion, with no obvious expansion of moderate and above erosion. Land use change significantly affects the intensity of water-induced soil erosion. The expansion of construction land mainly increases local slight and light erosion, while the increase in water areas, forest land, and wetlands effectively restrains moderate and high-intensity erosion and enhances regional soil conservation capacity.
文献参数: 冯子睿, 马波, 张秀梅, 等.2003—2023年土地利用类型变化对新疆土壤水力侵蚀的影响[J].水土保持通报,2026,46(3):369-382. Citation:Feng Zirui, Ma Bo, Zhang Xiumei, et al. Impacts of land use type changes on water-induced soil erosion in Xinjiang from 2003 to 2023 [J]. Bulletin of Soil and Water Conservation,2026,46(3):369-382.
土地利用/覆被变化(land use and land cover change, LUCC)通过影响植被覆盖度、根系结构以及土壤理化性质,调控地表径流形成过程与水土保持功能,是影响土壤水力侵蚀的重要人类驱动因素[3]。土地开发强度过高往往破坏地表结构,增加地表裸露度并增强径流侵蚀能力,从而加剧土壤侵蚀风险[4],尤其在干旱与半干旱地区表现更为突出。在土壤水力侵蚀的定量评估方面,修正通用土壤流失方程(revised universal soil loss equation, RUSLE)因其结构清晰,参数易获取,适用性强而被广泛应用[5]。该模型综合考虑降雨侵蚀力、土壤可蚀性、地形因子、植被覆盖及水土保持措施等关键因素,可估算区域尺度年均土壤侵蚀模数[6],在土壤侵蚀时空格局分析与水土保持规划中具有重要应用价值。已有研究表明,RUSLE模型在新疆及相似自然环境区具有较好的适用性。如熊茂秋等[7]研究发现,2000—2020年塔里木河流域土壤侵蚀面积总体呈缩小趋势,土壤保持能力显著增强,其空间分布格局表现为中部高、四周低,降雨与地形条件是主要驱动因素。Yan Zhaojin等[8]基于RUSLE模型揭示了天山北坡城市群2010—2020年土壤侵蚀的时空演变特征,并模拟了不同情景下土地利用变化对土壤侵蚀的潜在影响。
DuanJian, YangGe, WangYingying, et al. Impacts of terrestrial surface human activity intensity changes on ecological environment quality in the Nianchu River basin [J/OL]. Acta Ecologica Sinica, 2026,46(6):3160-3180.
WangXinyu, YaoWenzhuo. Study on spatial pattern of land use change and soil erosion in typical black soil region of northeast China: A case study of Nenjiang City [J]. Geomatics & Spatial Information Technology, 2025,48(S2):83-86.
HuXinyi, XiaoZuolin, QinChuan, et al. Multi-scenario prediction of land use changes and soil erosion in Three Gorges reservoir region based on PLUS-InVEST model [J]. Journal of Soil and Water Conservation, 2025,39(6):106-117.
PanWen, WangQiang. Review on the impact of the land use pattern and the strength on the soil corrosion resistance [J]. Subtropical Soil and Water Conservation, 2024,36(1):44-46.
ZhuangYongzai, HeGuangxiong, XiWenfei, et al. Spatiotemporal dynamics of cultivated land soil erosion in dry-hot valley ecosystems: An integrated assessment using RUSLE model and multi-source data [J]. Science of Soil and Water Conservation, 2025,23(6):42-53.
XieLe, HouPeng, LiuYisheng. Research progress of quantitative evaluation methods of soil and water loss based on soil loss equation [J]. Environmental Ecology, 2024,6(11):1-10.
XiongMaoqiu, LiuXiaohuang, ZhangXuehui, et al. Spatio-temporal variation of soil conservation in the upper reaches of the Tarim River basin based on RUSLE model [J]. Geological Bulletin of China, 2024,43(4):641-650.
[15]
YanZhaojin, MaoFulin, HeRong, et al. Spatial and temporal evolution and prediction of soil erosion in the urban agglomeration on the northern slopes of the Tianshan Mountains in China [J]. Geocarto International, 2025,40(1):2521834.
YueXiao, ZhangLiangxia, ZhouDecheng, et al. Spatial-temporal variations and driving forces of the ecological vulnerability in the typical arid/semi-arid ecologically vulnerable areas [J]. Environmental Ecology, 2023,5(6):1-9.
HeHaiyan, LiXiaoxia, WeiWei. Study on influencing factors of soil water erosion in China [J]. Journal of Agricultural Disaster Research, 2022, 12(6): 152-154.
[24]
梁靓.变化环境下西北干旱区土壤侵蚀演变及预测研究[D].甘肃 兰州:兰州理工大学,2024.
[25]
LiangLiang. Study on soil erosion evolution and prediction in arid area of northwest China under changing environment [D]. Lanzhou, Gansu: Lanzhou University of Technology, 2024.
LiNa, WangXinjun, LuGang, et al. Temporal and spatial changes of soil erosion in Xibaiyanggou watershed on the northern slope of Tianshan Mountains from 2000 to 2017 [J]. Journal of Arid Land Resources and Environment, 2021,35(3):73-79.
QiaoYuning, RenJingyu, WuRui, et al. Dynamic change of soil erosion and water loss in the Tarim River basin in Xinjiang [J]. Soil and Water Conservation in China, 2025(5):66-72.
ZhangXiaomin, ZhangDongmei, WangLi, et al. Soil erosion analysis in the Irtysh River basin under the combined effects of rainfall, snow cover and land use [J]. Journal of Soil and Water Conservation, 2022,36(5):104-111.
YaoJunqiang, LiMoyan, TuoliewubiekeDilinuer, et al. The assessment on “warming-wetting” trend in Xinjiang at multi-scale during 1961—2019 [J]. Arid Zone Research, 2022,39(2):333-346.
ZhangZhihao, HeBaozhong, SongYaning, et al. Multi-scenario analysis of land-use and habitat quality in Xinjiang based on SD-PLUS-InVEST [J]. Environmental Science & Technology, 2025,48(3):10-22.
[36]
WilliamsJ R. The erosion-productivity impact calculator (EPIC) model: A case history [J]. Philosophical Transactions of the Royal Society of London. Series B, 1990,329(1255):421-428.
CaiChongfa, DingShuwen, ShiZhihua, et al. Study of applying USLE and geographical information system IDRISI to predict soil erosion in small watershed [J]. Journal of Soil and Water Conservation, 2000,14(2):19-24.
ChenChaoliang, ZhaoGuangju, MuXingmin, et al. Spatial-temporal change of soil erosion in Huangshui watershed based on RUSLE model [J]. Journal of Soil and Water Conservation, 2021,35(4):73-79.
[43]
何源.窟野河流域土壤侵蚀时空特征及动态评价[D].陕西 杨凌:西北农林科技大学,2025.
[44]
HeYuan. Spatiotemporal characteristics and trend prediction of soil erosion in Kuye River basin [D]. Yangling, Shaanxi: Northwest A&F University, 2025.
Ministry of Water Resources of the People’s Republic of China. SL 190—2007 Standards for classification and gradation of soil erosion [S]. Beijing: China Water & Power Press, 2008.
ZhangLiangyu, LiXingyang, WangZhichao, et al. Spatial autocorrelation analysis of PM2.5 in Beijing-Tianjin-Hebei Region based on Moran’s I index [J]. Sichuan Environment, 2021,40(2):52-59.
ChenYanguang. Reconstructing the mathematical process of spatial autocorrelation based on Moran’s statistics [J]. Geographical Research, 2009,28(6):1449-1463.
HuangLu, DuYiqian, YangXiuchun. Evaluation of grassland ecological restoration effects in the grassland restoration project areas of Xinjiang [J/OL]. (2025-12-19). Acta Agrestia Sinica, 2025:1-22.
WangHaolin, JiaoJuying, AnShaoshan, et al. Investigation on soil erosion in north and south slopes of eastern Tianshan Mountain in Xinjiang Wei Autonomous Region [J]. Bulletin of Soil and Water Conservation, 2019,39(4):306-313.
GaoYang, NingLü, XueChongsheng, et al. Study on spatial relationship of land use and soil erosion of different regions [J]. Soil and Water Conservation in China, 2006(11):21-23.
LiYimin, ZhuJun. An assessment on toregional soil erosion sensitivity based on GIS: Taking Nujiang Prefecture as an area of study [J]. Journal of Yunnan University (Natural Sciences Edition), 2017,39(1):98-106.
DengXiangzheng, LiuYijie, LiuYuhan. Climate-vegetation threshold mechanism and temporal response characteristics of soil erosion in the Yellow River basin [J]. Yellow River, 2025,47(9):77-84.
LiJialei, SunRanhao, XiongMuqi, et al. Spatiotemporal patterns of soil water erosion in China based on the RUSLE model [J]. Acta Ecologica Sinica, 2020, 40(10): 3473-3485.
ZhangQiwang, AnJunzhen, WangXia, et al. Research progress of soil erosion related models in China [J]. Soil and Water Conservation in China, 2014 (1): 43-46, 69.
[65]
BorrelliP, RobinsonD A, FleischerL R, et al. An assessment of the global impact of 21st century land use change on soil erosion[J]. Nature Communications, 2017,8(1):2013.