Global Analysis of the Cover-Management Factor for Soil Erosion Modeling
文献类型：期刊论文
| 作者 | Xiong, Muqi; Leng, Guoyong; Tang, Qiuhong |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-05-31 |
| 卷号 | 15期号:11页码:2868 |
| ISSN号 | 2072-4292 |
| 关键词 | USLE RUSLE soil erosion land use and management practices C-factor |
| DOI | 10.3390/rs15112868 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Land use and management practices (LUMPs) play a critical role in regulating soil loss. The cover-management factor (C-factor) in Universal Soil Loss Equation (USLE)-type models is an important parameter for quantifying the effects of LUMPs on soil erosion. However, accurately determining the C-factor, particularly for large-scale assessments using USLE-type models, remains challenging. This study aims to address this gap by analyzing and comparing the methods used for C-factor quantification in 946 published articles, providing insights into their strengths and weaknesses. Through our analysis, we identified six main categories of methods for C-factor quantification in USLE-type modeling. Many studies have relied on empirical C-factor values for different land-use types or calculated C-factor values based on vegetation indices (VIs) in large study areas (>100 km(2)). However, we found that no single method could robustly estimate C-factor values for large-scale studies. For small-scale investigations, conducting experiments or consulting the existing literature proved to be more feasible. In the context of large-scale studies, employing methods based on VIs for C-factor quantification can enhance our understanding of the relationship between vegetation changes and soil erosion potential, particularly when considering spatial and spatiotemporal variations. For the global scale, we recommend the combined use of different equations. We suggest further efforts to develop C-factor datasets at large scales by synthesizing field-level experiment data and combining high-resolution satellite imagery. These efforts will facilitate the development of effective soil conservation practices, ensuring sustainable land use and environmental protection. |
| 学科主题 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS关键词 | GIS-BASED RUSLE ; WATER EROSION ; LAND-USE ; CLIMATE-CHANGE ; LOSS EQUATION ; SEDIMENT DELIVERY ; RISK-ASSESSMENT ; RAINFALL EROSIVITY ; ECOSYSTEM SERVICES ; DISTRIBUTED MODEL |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/193775]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 作者单位 | 1.Institute of Geographic Sciences & Natural Resources Research, CAS 2.Chinese Academy of Sciences 3.University of Chinese Academy of Sciences, CAS |
| 推荐引用方式 GB/T 7714 | Xiong, Muqi,Leng, Guoyong,Tang, Qiuhong. Global Analysis of the Cover-Management Factor for Soil Erosion Modeling[J]. REMOTE SENSING,2023,15(11):2868. |
| APA | Xiong, Muqi,Leng, Guoyong,&Tang, Qiuhong.(2023).Global Analysis of the Cover-Management Factor for Soil Erosion Modeling.REMOTE SENSING,15(11),2868. |
| MLA | Xiong, Muqi,et al."Global Analysis of the Cover-Management Factor for Soil Erosion Modeling".REMOTE SENSING 15.11(2023):2868. |
入库方式： OAI收割
来源：地理科学与资源研究所
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