Applicability Evaluation and Correction of Cover and Management Factor Calculation Methods in the Purple Soil Hilly Region
Ruiyin Chen (),
Yonggang Zhu,
Derong Wu,
Jia Zhong (),
Anbang Wen,
Wenwu Wang,
Biao Bi,
Yuetian Li,
Jing Feng and
Tiancai Jing
Additional contact information
Ruiyin Chen: Key Laboratory of Mountain Surface Process and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
Yonggang Zhu: POWERCHINA Chengdu Engineering Corporation Limited, Chengdu 611130, China
Derong Wu: POWERCHINA Chengdu Engineering Corporation Limited, Chengdu 611130, China
Jia Zhong: School of Emergency Management, Xihua University, Chengdu 610039, China
Anbang Wen: Key Laboratory of Mountain Surface Process and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
Wenwu Wang: POWERCHINA Chengdu Engineering Corporation Limited, Chengdu 611130, China
Biao Bi: POWERCHINA Chengdu Engineering Corporation Limited, Chengdu 611130, China
Yuetian Li: POWERCHINA Chengdu Engineering Corporation Limited, Chengdu 611130, China
Jing Feng: POWERCHINA Chengdu Engineering Corporation Limited, Chengdu 611130, China
Tiancai Jing: POWERCHINA Chengdu Engineering Corporation Limited, Chengdu 611130, China
Agriculture, 2025, vol. 15, issue 9, 1-20
Abstract:
The cover and management factor (C/B factor) in the Universal Soil Loss Equation (USLE) series models indicates the effects of vegetation cover and management practices on water erosion. Remote sensing technology provides abundant data and methods for the C/B factor estimation, but the applicability and accuracy of these methods can vary widely. More critically, they often overlook the impact of non-photosynthetic vegetation cover on soil erosion. This study aimed to evaluate and develop a more accurate and cost-effective method for calculating the C/B factor in the purple soil hilly region, focusing on typical small watersheds. A correlation analysis was conducted to compare four C/B factors derived from the remote sensing data, aiming to identify the most suitable method for the purple soil hilly region. Additionally, artificial rainfall simulation tests were performed to investigate the relationship between photosynthetic vegetation cover, non-photosynthetic vegetation cover, and soil erosion, leading to the development of a relational equation between integrated vegetation cover and C/B factors. The results indicate that the method from the technical regulations for dynamic monitoring of soil erosion is most suitable for calculating the C/B factor in purple soil hilly regions. On this basis, the integrated vegetation cover effectively accounted for the impact of non-photosynthetic vegetation on soil erosion, leading to a more comprehensive and precise estimation of the C/B factor. The newly developed method significantly improved the accuracy of the C/B factor calculation in the purple soil hilly region. This study provides a scientific and accurate algorithm for calculating the C/B factor in the purple soil hilly region, offering valuable insights and a methodological framework for similar studies in other areas.
Keywords: purple soil hilly region; cover and management factor; photosynthetic vegetation cover; non-photosynthetic vegetation cover (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2077-0472/15/9/941/pdf (application/pdf)
https://www.mdpi.com/2077-0472/15/9/941/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:15:y:2025:i:9:p:941-:d:1643062
Access Statistics for this article
Agriculture is currently edited by Ms. Leda Xuan
More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().