The sediment transport capacity must be considered because it provides a theoretical basis for accurate prediction of soil erosion. Existing studies tended to study sediment transport capacity using a particular soil, but the models derived from one kind of soil cannot be applicable to other soil types. To obtain a prediction model for a variety of soils and evaluate its applicability, sandy loess and loess soil (d50=0.095 mm and d50’=0.04 mm) were chosen in the indoor artificial simulated sediment transport experiments. The experimental slopes ranged from 7% to 38.4% and the unit discharges were adjusted from 0.00014 to 0.00526m2/s. Moreover, this study combined the experimental data with cohesive soil and cohesionless sand from four scholars so as to analyze the response relationship between sediment transport capacity and each flow intensity parameter through dimensionless processing. Results showed that the dimensionless sediment transport capacity varied with its power function relationship with the flow intensity parameters. Through analysis, the effective stream power could be seen as an optimum indicator (R2=0.9692). After considering the effective stream power and volume sediment concentration, this study derived a formula for calculating the sediment transport capacity. It was better than the ANSWERS (Areal Nonpoint Source Watershed Environment Response Simulation) model, improved WEPP (Water Erosion Prediction Project) model, Zhang’s formula and Ali’s model due to its superior applicability to cohesive soil and cohesionless sand. These findings lay a basis for establishing prediction models of soil erosion.

Overland flow is the major contributor to soil erosion. To clarify the hydrodynamic characteristics of overland flow at small Reynolds number, indoor experiments with fifteen unit-width flow discharges from 0.069 × 10-3 m2·s-1 to 2.5 × 10-3 m2·s-1, five slope gradients from 5.23% to 25.88%, three surface roughnesses and two kinds of flow (80% glycerol and water mixed flow and water flow) were systematically investigated. Results showed that mean depth and mean flow velocity can be good predicted by unit-width flow discharge, slope gradient and surface roughness. Based on flow regime criterion of parameter m, for 80% glycerol and water mixed flow, the flow regime was laminar flow. For water flow, it was between laminar flow and turbulent flow. According to the transitional Fr of 1, the experimental flow state tended to subcritical laminar flow with the increase of surface roughness. For 80% glycerol and water mixed flow, parameter K was 57. For water flow, parameter K was increased with the increase of surface roughness and fluctuated as slope gradient increased. The resistance law of open channel hydraulic for laminar flow (f = 96/Re) is not suitable for overland flow. In general, resistance coefficient had a good power function with Re. Meanwhile, there was a high significant correlation between resistance coefficient and inundation ratio and slope gradient. Resistance coefficient decreased as inundation ratio and slope gradient increased. For all flow regime in this study, a more accurate resistance coefficient prediction model was established by multiple regression analysis. As for hydrodynamic parameters, shear stress had a positive correlation with surface roughness. Meanwhile, stream power is not affected by increasing surface roughness, while unit stream power was negative with surface roughness. The slope gradient played a more important role in increasing the flow energy.