## 3 Results and Discussion
### RUSLE Model
#### 3.1.6. RUSLE Model
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Land Cover Class**} & \multicolumn{4}{c}{**Mean Annual Soil Loss (t ha\({}^{-1}\) Year\({}^{-1}\))**} \\ \cline{2-5}  & **Scenario 1** & **Scenario 2** & **Scenario 3** & **Scenario 4** \\ \hline Agricultural areas & 5.882 & 5.642 & 6.873 & 5.253 \\ Forest & 0.145 & 1.452 & 8.932 & 0.835 \\ Natural grassland and pasture & 3.064 & 5.241 & 5.809 & 2.896 \\ Shrubland & 0.912 & 4.950 & 11.381 & 2.491 \\ Sparsely vegetated areas & 37.927 & 4.693 & 4.142 & 0.864 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Soil erosion rates in terms of land cover. their assessment, the mean annual soil loss rate was found to be 8.123 t ha\({}^{-1}\). The mean erosion rate for sparsely vegetated areas was the highest, followed by natural grassland and pasture, shrubland, agricultural areas, and forest areas. Consequently, both scenario 3 and scenario 4, which presented low values for sparsely vegetated areas, were excluded. A cell-by-cell analysis of the soil loss map showed that the highest soil loss values were positively correlated with the steepest slopes. This finding was confirmed with reference to the study by [PERSON] et al. [3] in Chania, Crete; however, in this study, the correlation was higher for scenario 2 than scenario 1, meaning scenario 2 was considered to provide the most reliable results for soil loss estimation. Soil loss values were calculated by overlaying five grid rasters (a grid raster representing R-factor values estimated from rain gauge data, a grid raster representing K-factor values, a grid raster representing LS-factor values, a grid raster representing C-factor values, and a grid raster representing P-factor values). The final maps produced to show the spatial distribution of annual soil loss within the study area at 10 m pixel resolution were as follows:  
* Scenario 5: A soil loss map was produced with R-factor values derived from in situ data and C-factor values assigned from literature data (Figure 20);
* Scenario 6: A soil loss map was produced with R-factor values derived from in situ data and C-factor values derived from _NDVI_ (exponential (_NDVI_-vk)) data (Figure 21). Figure 20: Soil loss map with R-factor values derived from in situ data and C-factor values derived from literature data. According to scenario 5, the estimated soil loss ranged from 0 to 279 t ha\({}^{-1}\) year\({}^{-1}\), with a mean value of 1.95 t ha\({}^{-1}\) year\({}^{-1}\). According to scenario 6, the estimated soil loss ranged from 0 to 583 t ha\({}^{-1}\) year\({}^{-1}\), with a mean value of 3.24 t ha\({}^{-1}\) year\({}^{-1}\). Table 10 lists the values for the mean annual soil loss with R-factor values derived from GPM data and rain gauge data and C-factor values derived from literature and NDVI data, respectively. The annual soil erosion rates obtained using R-factor values derived from rain gauge data were slightly underestimated in comparison with those obtained using R-factor values derived from GPM data. This underestimation was due to the differences in the data used to derive R-factor values (satellite-based data vs. ground-based data).