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作 者:王淼 牛健植[1,2,3,4] 杨涛 王迪 苗禹博 贾梦柔 WANG Miao;NIU Jianzhi;YANG Tao;WANG Di;MIAO Yubo;JIA Mengrou(School of Soil and Water Conservation,Beijing Forestry University,100083,Beijing,China;State Key Laboratory of Efficient Production of Forest Resources,100083,Beijing,China;Key Laboratory of State Forestry Administration on Soil and Water Conservation and Desertification Combating,100083,Beijing,China;Engineering Research Center of Forestry Ecological Engineering of Ministry of Education,Beijing Forestry University,100083,Beijing,China;Academy of Forestry Inventory and Planning,National Forestry and Grassland Administration of P.R.China,100714,Beijing,China)
机构地区:[1]北京林业大学水土保持学院,北京100083 [2]林木资源高效生产全国重点实验室,北京100083 [3]水土保持与荒漠化防治国家林业局重点实验室,北京100083 [4]林业生态工程教育部工程研究中心,北京100083 [5]国家林业和草原局林草调查规划院,北京100714
出 处:《中国水土保持科学》2025年第2期55-65,共11页Science of Soil and Water Conservation
基 金:国家重点研发计划项目“黄河中游多沙粗沙区风水复合侵蚀协同治理技术与示范”(2022YFF1300804)。
摘 要:黄河中游多沙粗沙区土壤侵蚀十分严重。为明晰区域土壤侵蚀发生的潜在几率,笔者应用修正通用土壤流失方程(RUSLE)与ArcGIS,综合评价土壤侵蚀敏感性(2010、2015和2020年),并识别敏感性关键因子。结果如下:1)研究区土壤侵蚀敏感性整体由东南至西北呈现降低趋势,中部、东部地区为极敏感和高度敏感主要分布区。2)2010—2020年土壤侵蚀敏感性整体上表现为先增后减。研究区西侧敏感性等级较低,研究区南部、北部以及东部偏南区域表现出较为明显的等级降低,约占研究区面积的21%;东南部与东部偏北区域敏感性等级有所增加,约占研究区面积的15.8%。3)植被覆盖度C因子主要在不敏感具有较大影响;土壤可蚀性K因子控制着研究区中部与东部绝大部分区域,主要为轻度及以上敏感等级,在各影响因子排序中均>90%;降雨侵蚀力R因子在研究区东部与西部对植被覆盖不足与土壤破坏严重地区具有较大影响;地形起伏度LS因子对整个研究区土壤侵蚀的影响较小。此结果可为未来区域防治、水土保持治理规划提供理论支撑。[Background]The plentiful and coarse sediment area of the middle Yellow River is the main source of sediment,and the annual average sediment transport load is 1.182 billion tons,accounting for 73.9%of the total sediment flow into the Yellow River.Soil erosion in this area is very serious and the ecological environment is fragile,causing heavy ecological pressure,which not only threatens the local ecological security,but also has a great impact on the downstream river,posing a serious threat to human production and life.[Methods]In order to quantify the potential probability of regional soil erosion and identify the key factors of soil erosion,revised universal soil loss equation(RUSLE)and ArcGIS technology were applied in this study to comprehensively evaluate the sensitivity of soil erosion.The key sensitivity factors were also identified by superposition ranking analysis(2010,2015,and 2020).Visualization of the spatial and temporal distribution of soil erosion sensitivity and key sensitivity factors was achieved.[Results]1)Soil erosion sensitivity showed a decreasing trend from southeast to northwest.The extremely sensitive and highly sensitive areas were mainly found in the central and eastern parts of the study area,while moderate sensitive areas showed a large staggered distribution.2)From 2010 to 2020,the overall soil erosion sensitivity increased first and then decreased.The west of the study area showed relatively stable low sensitivity,the south,north and some eastern regions of the study area showed a relatively obvious decline,mainly due to the increase of insensitive(6.0%),and the southeast and other eastern areas of the study area increased,mainly due to the expansion of highly sensitive and extremely sensitive areas(1.2%).3)C factor mainly had a great influence in insensitive areas;K factor controlled most of the central and eastern regions of the study area with the grade higher than slightly sensitive.In the western part of the study area,the combination of R and C factor increased the risk of soi
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