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Frontiers of Earth Science

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Front. Earth Sci.    2020, Vol. 14 Issue (3) : 660-672    https://doi.org/10.1007/s11707-020-0828-y
RESEARCH ARTICLE
Developing a USLE cover and management factor (C) for forested regions of southern China
Conghui LI1, Lili LIN1,2, Zhenbang HAO1,2, Christopher J. POST3, Zhanghao CHEN1,2, Jian LIU1,2, Kunyong YU1,2()
1. Fujian Agriculture and Forestry University, Fuzhou 350002, China
2. University Key Laboratory for Geomatics Technology and Optimized Resources Utilization in Fujian Province, Fuzhou 350002, China
3. Department of Forestry and Environmental Conservation, Clemson University, Clemson SC 29634, USA
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Abstract

The Universal Soil Loss Equation model is often used to improve soil resource conservation by monitoring and forecasting soil erosion. This study tested a novel method to determine the cover and management factor (C) of this model by coupling the leaf area index (LAI) and soil basal respiration (SBR) to more accurately estimate a soil erosion map for a typical region with red soil in Hetian, Fujian Province, China. The spatial distribution of the LAI was obtained using the normalized difference vegetation index and was consistent with the LAI observed in the field (R2 = 0.66). The spatial distribution of the SBR was obtained using the Carnegie–Ames–Stanford Approach model and verified by soil respiration field observations (R2 = 0.51). Correlation analyses and regression models suggested that the LAI and SBR could reasonably reflect the structure of the forest canopy and understory vegetation, respectively. Finally, the C-factor was reconstructed using the proposed forest vegetation structure factor (Cs), which considers the effect of the forest canopy and shrub and litter layers on reducing rainfall erosion. The feasibility of this new method was thoroughly verified using runoff plots (R2 = 0.55). The results demonstrated that Cs may help local governments understand the vital role of the structure of the vegetation layer in limiting soil erosion and provide a more accurate large-scale quantification of the C-factor for soil erosion.
Keywords leaf area index      remote sensing      soil basal respiration      forest vegetation structure factor      vegetation layer structure     
Corresponding Author(s): Kunyong YU   
Online First Date: 23 November 2020    Issue Date: 04 December 2020
 Cite this article:   
Conghui LI,Lili LIN,Zhenbang HAO, et al. Developing a USLE cover and management factor (C) for forested regions of southern China[J]. Front. Earth Sci., 2020, 14(3): 660-672.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-020-0828-y
https://academic.hep.com.cn/fesci/EN/Y2020/V14/I3/660
Fig.1  Schematic of a vegetation plot (a) with understory vegetation and (b) without understory vegetation.
Fig.2  Study area and location of the sampling plots.
Fig.3  Flowchart of the method to determine the proposed C-factor.
Fig.4  Flowchart of net primary productivity estimation.
Data set Description Data source
Pleiades satellite images December 10, 2014; 2 m spatial resolution multispectral data and 0.5 m spatial resolution panchromatic data; view number 0719-04222 and 0519-03996 France (available at L3Harris Geospatial website)
Meteorological data Data were used to calculate net primary productivity, including mean monthly temperature, precipitation, multi-year mean precipitation, and solar radiation Changting County Meteorological Bureau
Soil respiration Measured by Li-8100A Carbon Flux Automatic Measurement System (LiCOR, USA) and used to verify the soil basl respiration inversion Field survey
Leaf area index Measured by LAI-2200 plant canopy analyzer (PCA, USA) and used to verify LAI inversion Field survey
Runoff plot data Observation data from runoff plots in Weifang watershed Fujian Soil and Water Conservation Monitoring Station
Tab.1  Description of study data
Model Tree, shrub, and litter control model Shrub and litter control model Litter clearance model (shrub control model) Farmland management model
Runoff depth/mm 81.4 89.1 123.7 142.4
Tab.2  Runoff depth observations in Weifang using different models
VI Model type Estimation model Validation indicators
R2 RMSE MRA MEA
RVI Linear y=0.983x-0.594 0.63 0.51 78.83% 96.37%
RVI Logarithmic Y=3.289lnx-1.255 0.62 0.57 81.35% 97.85%
RVI Quadratic y=-0.005x2+0.977x-0.661 0.63 0.51 78.97% 96.37%
NDVI Power y=7.895x1.791 0.66 0.59 82.99% 98.14%
NDVI Exponential y=0.351e3.656x 0.65 0.52 82.48% 99.66%
Tab.3  The best inversion results of leaf area index (LAI) in each model type
Fig.5  Distribution of leaf area index.
Forest type Sample (n) Measured Rs /(μmol·m−2·s−1) Estimated Rs /(μmol·m−2·s−1) MRA MEA
Min Mean Max Min Mean Max
Masson pine 59 0.37 0.95 1.76 0.45 0.92 1.82 77.83% 97.27%
Tab.4  Accuracy evaluation of soil respiration (Rs) model for Masson pine plantations
Fig.6  Maps of (a) net primary productivity (NPP) distribution and (b) soil basal respiration (SBR) distribution.
Fig.7  Comparison of measured and estimated soil respiration rates (µmol·m−2·s−1).
Factor LLT UVC SBR
LLT 1 0.457** 0.527**
UVC − 1 0.729**
SBR − − 1
Tab.5  Correlations between litter layer thickness (LLT), understory vegetation coverage (UVC), and soil basal respiration (SBR)
Factor Best-fit model RMSE MRA MEA
UVC y=0.173x+7.440 1.67 84.42% 98.04%
LLT y=1.294+6.925 1.96 84.39% 97.31%
Tab.6  Assessment of models for litter layer thickness (LLT) and understory vegetation coverage (UVC)
Item Tree Shrub and grass Litter
Reduction ratio/% 5.41 13.13 24.30
Reduction flow coefficient of unit coverage 0.090 0.164 0.243
Weight 0.181 0.330 0.489
Tab.7  Weights of forest vertical structure
Fig.8  C-factor map determined from leaf area index (LAI) and soil basal respiration (SBR).
Fig.9  Relationship between C-factor and soil erosion in study area.
Fig.10  C-factor map based on (a) Normalized difference vegetation index (NDVI) and (b) Leaf area index (LAI).
Fig.11  Relationship between soil erosion and C-factor determined by (a) Normalized difference vegetation index (NDVI) and (b) Leaf area index (LAI).
Relationship equations of other researchers Validation at Weifang watershed
References Relationship equations R2
Bu et al. (1993) C = 0.450-0.00786 fc 0.423
Jiang et al. (1996) C = exp[-0.0085(fc -5)1.5]; fc>5%
C = 1; fc≤5%		 0.269
Cai et al. (2000) C = 1; fc = 0
C = 0.6508-0.3436lg fc; 0<fc<78.3%
C = 0; fc≥78.3%		 0.483
Jiang (2005) C = 1; fc = 0
C = 0.6665-0.3436 lg fc; 0<fc<87%
C = 0; fc>87%		 0.359
Tab.8  Validation of the relationship equations between the C-factor and vegetation coverage
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