Developing new equations for estimating cover-management factor in fire-affected forest lands in west north of the Guilan province

The correct estimation of cover-management (C) factor for accurate evaluating of soil loss is essential. Because of spatial variations in soil erosion parameters and vegetation attributes in large areas, the possibility of applying the available tables and regression equations to estimate the C-factor to other regions is limited. Up to this time, no studies have been done to estimate the C-factor in the forests of northern Iran. The main objective of this study was to develop new equations to estimate the C-factor in some parts of forest lands of the Guilan province using remote sensing methods and field works.
In parcels separated in 15 fire-affected sites and 15 original forests beside the burned (unburned) sites, in five sub land units, some vegetation attributes, soil properties and erosion rate were measured. The soil erosion was also estimated for all 30 studied parcels using the Revised Universal Soil Loss Equation (RUSLE) model. The actual C-factor were extracted for all the studied parcels (burned and unburned sites) using the measured (observed) erosion and other factors used in the RUSLE model. A split-plot in space design was performed to determine whether the differences between five sub land units (between subjects) and also within burned and control (unburned) sites (within subjects) were significant.
The results showed that the average of the actual C-factor in unburned and burned sites in five sub land units depending on plant density and disturbance of forest lands by fire severity and human and animal activity were between 0.05 to 0.14 and 0.13 to 0.24, respectively. In general, the estimated C-factor was more than the actual C-factor in all the studied sites. Moreover, the results of analysis of variance showed that damaging of trees by fire had significant effect on the estimated C-factor, actual C-factor, estimated erosion, measured erosion and soil erodibility factor. To develop new equations for estimating the C-factor, the correlations between the actual C-factor and some vegetation attributes and soil moisture characteristics were investigated. First of all, the relationship between the actual C-factor and the Normalized Difference Vegetation Index was derived as a new equation to estimate the C-factor in the study area. Then, the results of Multiple Linear Regression by stepwise method showed that among all the variables related to vegetation and soil moisture, the thickness of surface litter, canopy cover, diameter of trees at breast height, saturated water content and Permanent Wilting Point were the best variables to estimate the C-factor in the study area.
The soil erosion assessment using available models to estimate the C-factor had no adequate accuracy and caused errors in soil loss estimation. The models derived in this paper can be used for accurate estimation of the C-factor in other areas having similar crop attributes.