Adapting the WEPP Hillslope Model and the TLS Technology to Predict Unpaved Road Soil Erosion.

Unpaved road erosion have been recognized as important sediment sources in a watershed. To evaluate where and when road erosion occurs, the soil loss along road segments should be precisely predicted with process-based erosion models. Methods: The hillslope version of the Water Erosion Prediction Project (WEPP) was used to estimate soil loss from 20 typical road segments in the red soil region of South China. Terrestrial laser scanning (TLS)-measured soil losses were used to validate the model simulations. The results showed that the WEPP model could reasonably predict the total soil loss in relatively short (less than 100 m) and gentle (slope gradient lower than 10%) road segments. In contrast, soil loss would be underestimated for long or steep road segments. Detailed outputs along roads revealed that most of the peak soil loss rates were underestimated. It might due to the linear critical shear stress theory in the WEPP model. Additionally, the lack of upstream flow was found to be connected to the relatively low model efficiency. Nevertheless, the WEPP simulation could accurately fit erosion trend and predict the peak soil loss positions along road segments. Conclusions: The WEPP model could be adopted to evaluate the erosion risk of unpaved roads in the red soil region of South China.

Spatial distribution and risk assessment of heavy metals inside and outside a typical lead-zinc mine in southeastern China.

Mining activity is an important source of heavy metals in soil. Understanding the contents and distribution of heavy metals in mineral-waste soil and surrounding environments is important for the rational management of mines and reducing the migration of heavy metals to surrounding environments. We used a non-ferrous metal mine in southern China as a research object. Three types of sampling site (A-C) were established on the mineral-waste soil in the mining area and on nearby farmland (D) and along a river channel (E) outside the mining area: A, newly processed mineral-waste soil; B, steep 6-month-old stack of waste soil; C, gentle slope of 12-month-old waste soil; D, farmland soil within 1 km of the mine; and E, river water and adjacent soil. Soil samples were collected from the 0-10-cm layer at each site type. The contents and spatial distribution of Pb, Zn, and Cd at the sampling sites were analyzed, and the environmental risks were evaluated. The mean Pb, Zn, and Cd contents in the mining area (types A-C) were 2028, 3794, and 14.8 mg kg-1, respectively, which were 8-, 19-, and 49-fold higher than the second-level limits of the Environmental Quality Standard for Soils of China, and the mean contents of Pb, Zn, and Cd for sites D and E were 76.4, 131, and 0.18 mg kg-1 and 147, 194, and 0.95 mg kg-1, respectively, all of which were under the second-level limits. Sites C and E were also used to analyze the spatial distribution of the Pb, Zn, and Cd contents. Geostatistical analysis found that the Pb, Zn, and Cd contents had a clear and similar spatial pattern at site C and generally decreased from north to south. Soil Pb, Zn, and Cd contents at site E generally increased, and water Pb, Zn, and Cd concentrations decreased along the river channel. The soils at site types A-C in the mining area were heavily polluted, with a high potential threat to the surrounding environment, and the farmland and river-bank soils at D and E were free of pollution or were lightly polluted, with low potential ecological risks. This study provides a scientific basis and supporting data for heavy-metal treatment in mining areas.