湖北农业科学 ›› 2025, Vol. 64 ›› Issue (9): 27-35.doi: 10.14088/j.cnki.issn0439-8114.2025.09.006

• 资源·环境 • 上一篇    下一篇

地貌敏感区土壤保持的长期演变及其气候时空响应机制——以山西省为例

陈晓文1, 荀佳常1, 刘昌永2, 张鹤缤1, 王晓娅1   

  1. 1.中国冶金地质总局第三地质勘查院,太原 030032;
    2.中国冶金地质总局三局,太原 030032
  • 收稿日期:2025-07-23 出版日期:2025-09-25 发布日期:2025-10-28
  • 通讯作者: 荀佳常,陕西汉中人,主要从事地理信息、地质灾害研究,(电子信箱)3255410357@qq.com。
  • 作者简介:陈晓文(1993-),男,山西大同人,工程师,主要从事矿山地质、地质灾害研究,(电子信箱)1522711952@qq.com。
  • 基金资助:
    北京师范大学环境变化与自然灾害教育部重点实验室项目(2022-KF-13)

Long-term evolution of soil conservation and its climatic spatio-temporal response mechanism in geomorphologically sensitive areas:A case of Shanxi Province

CHEN Xiao-wen1, XUN Jia-chang1, LIU Chang-yong2, ZHANG He-bin1, WANG Xiao-ya1   

  1. 1. The Third Geological Survey Institute of China General Administration of Metallurgical Geology, Taiyuan 030032, China;
    2. Third Bureau of China Metallurgical Geology Bureau, Taiyuan 030032, China
  • Received:2025-07-23 Published:2025-09-25 Online:2025-10-28

摘要: 以山西省为研究区域,基于2001—2023年多源遥感与气候数据构建RUSLE模型,并结合Theil-Sen Median趋势分析法、随机森林模型与逐像元回归方法,从空间与时间2个维度系统识别土壤保持变化的主控因子。结果表明,山西省2001—2023年土壤保持量总体呈显著上升趋势,年均增加0.149 t/hm2;潜在土壤侵蚀量和土壤保持量变化的高值区集中分布于地形起伏大、生态工程干预显著区域,表现出明显的地貌-气候耦合效应。驱动因素识别结果显示,土壤水分、风速和潜在蒸散发是空间维度上的关键控制变量,对随机森林模型的最大贡献解释度分别达20.0%、16.3%和15.5%;在时间维度上,干旱指数为主导因子,反映出水分亏缺对土壤保持年际变化的长期调控效应。

关键词: 土壤保持, 气候变化, RUSLE模型, 时空响应机制, 地貌敏感区, 山西省

Abstract: Taking Shanxi Province as the research area, based on multi-source remote sensing and climate data from 2001 to 2023, the RUSLE model was constructed, and the main controlling factors of soil conservation changes from both spatial and temporal dimensions were systematically identified by integrating Theil-Sen Median trend analysis method, random forest model, and pixel-by-pixel regression method. The results showed that the total soil conservation in Shanxi Province showed a significant upward trend from 2001 to 2023, with an average annual increase of 0.149 t/hm2. The high-value areas of changes in potential soil erosion and conservation were concentrated in regions with large topographic relief and significant ecological engineering intervention, showing an obvious geomorphology-climate coupling effect. The results of driving factor identification indicated that soil moisture, wind speed, and potential evapotranspiration were the key control variables in the spatial dimension, and the maximum contribution to the random forest model was 20.0%, 16.3% and 15.5%, respectively. In the temporal dimension, the drought index was the dominant factor, reflecting the long-term regulatory effect of water deficit on the interannual changes of soil conservation.

Key words: soil conservation, climate change, RUSLE model, spatio-temporal response mechanism, geomorphic sensitive areas, Shanxi Province

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