Global Analysis of the Cover-Management Factor for Soil Erosion Modeling
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-fact...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/11/2868 |
| _version_ | 1797596803317628928 |
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| author | Muqi Xiong Guoyong Leng Qiuhong Tang |
| author_facet | Muqi Xiong Guoyong Leng Qiuhong Tang |
| author_sort | Muqi Xiong |
| collection | DOAJ |
| description | 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<sup>2</sup>). 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. |
| first_indexed | 2024-03-11T02:58:10Z |
| format | Article |
| id | doaj.art-ed7499b89c1b4e36b668e7561dfc8069 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T02:58:10Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ed7499b89c1b4e36b668e7561dfc80692023-11-18T08:29:49ZengMDPI AGRemote Sensing2072-42922023-05-011511286810.3390/rs15112868Global Analysis of the Cover-Management Factor for Soil Erosion ModelingMuqi Xiong0Guoyong Leng1Qiuhong Tang2Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaLand 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<sup>2</sup>). 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.https://www.mdpi.com/2072-4292/15/11/2868USLERUSLEsoil erosionland use and management practicesC-factor |
| spellingShingle | Muqi Xiong Guoyong Leng Qiuhong Tang Global Analysis of the Cover-Management Factor for Soil Erosion Modeling Remote Sensing USLE RUSLE soil erosion land use and management practices C-factor |
| title | Global Analysis of the Cover-Management Factor for Soil Erosion Modeling |
| title_full | Global Analysis of the Cover-Management Factor for Soil Erosion Modeling |
| title_fullStr | Global Analysis of the Cover-Management Factor for Soil Erosion Modeling |
| title_full_unstemmed | Global Analysis of the Cover-Management Factor for Soil Erosion Modeling |
| title_short | Global Analysis of the Cover-Management Factor for Soil Erosion Modeling |
| title_sort | global analysis of the cover management factor for soil erosion modeling |
| topic | USLE RUSLE soil erosion land use and management practices C-factor |
| url | https://www.mdpi.com/2072-4292/15/11/2868 |
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