Abstract
Erosion is the main cause of damage to unpaved roads. This study utilized rainfall simulators to quantify erosion on unpaved roads, controlling variables such as rainfall intensity and slope. A laboratory model of an unpaved road was utilized to evaluate soil loss in an experimental setup. A total of 72 tests were conducted to compare simulated conditions on unpaved roads for three soil types with three slope variations, and eight rainfall intensities. The impact of each variable (soil type, slope, and rainfall intensity) on soil loss was analyzed for 30-minute rainfall events. Analysis of variance (ANOVA) was employed to assess soil erosion response to terrain slope for the three soil types, revealing statistical differences in soil loss between low slopes (2%) and steep slopes (7%) with p-values of .04 (sandy soil), .00007 (sandy silt soil), and .00008 (loam silt soil). Correlation analysis demonstrated a strong relationship between rainfall intensity and soil loss ( R2 = .76) for sandy soil and sandy silt soil. Analysis of covariance (ANCOVA) indicated a linear relationship between soil loss and rainfall intensity, with significant differences ( p < .05). The findings suggest that soil loss on unpaved roads is positively correlated with slope and rainfall intensity. However, this relationship is not always linear; sandy soil exhibited a nonlinear relationship, especially with high rainfall intensities, whereas sandy silt soil showed a linear relationship with evaluated rain intensities. The type of soil influences erosion process, with higher erosion rates observed in sandy silt soils compared to loam silt soils. This paper analyzed the factors essential for addressing erosion on unpaved roads, identifying key elements to minimize soil loss.
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