Acknowledgements

that the model did not accurately predict the solute concentrations of the runoff in conditions

Comparisons between the simulated and the experimental solute concentrations for the different rainfall intensities over 60 min are shown in Figure 18B. At a rainfall intensity of 129 mm/h, the solute concentration of the runoff increased substantially between 37 and 49 min after the initial generation of the runoff (Figure 18B). The mass of sediment in the runoff between 37 and 43–49 min showed a corresponding spike (Figure 19), which indicated that solute loss is closely related to sediment loss [41–45]. These results indicated that significant erosion of the surface soil occurred at the bottom of the slope during the experiments. Deeper soil layers were exposed to water in which the solute concentrations were higher than in those washed away. Consequently, the solute concentration of the runoff increased as these solutes were transferred from the soil under the influence of the runoff and the splashing caused by raindrops. Soil

Figure 18C shows that the measured and simulated solute concentrations for different slope gradients also changed with time. The simulated data were highly correlated with the measured data for solute concentration in the runoff. This degree of correlation demonstrated that the model captured the temporal behavior of the solute transport in the runoff. Increasing the gradient of the slope increased the erosion capacity of rain drops and water flow. Increasing

the relationships between potassium concentrations observed in the runoff and predicted using Eq. (26). The graph indicates the model accurately predict the solute transport in the

In order to understand the whole process of water-solute-heat transport and nutrient loss, we determined water movement, solute, and heat transport through columns of disturbed soil samples. And we also carried out simulated rainfall experiments on an artificial slope to study

1. Data obtained with experimental infiltration under negative hydraulic heads were employed to analyze the relationship between the Philip model and Kostiakov empirical model, showing as well that they were identical in terms of negative hydraulic heads; Wang's equation

2. The Horton empirical model can be used to describe the variation of soil thermal conductivity; the calculated values of Campbell model and Johansen model have large differences with the measured values. However, the calculated results of Côté-Konrad model and Lu-Ren model are in good agreement with the measured values. The improved Côté-Konrad model and improved Lu-Ren model can use the soil texture to predict soil thermal conductivity. For two improved models, the coefficients of determination R2 are above 0.92 and the relative errors Re are less than 9.6%. For the soils with high sand content or silt

. Figures 20 and 21 show

erosion thus promoted increased solute concentrations in the runoff.

the slope gradient also led to increases in the RMSE (Table 10) and R2

runoff with the solute concentration being at a much lower level.

could describe the infiltration process very well.

of severe soil erosion.

160 Hydrology of Artificial and Controlled Experiments

4. Conclusions

nutrient loss.

The results were as follows:

This study was financially supported by the National Natural Science Foundation of China (grant nos. 51239009, 41371239), Science and Technology Planning Project of Shaanxi Province (2013kjxx-38), and Doctoral fund of Xi'an University of Technology (106-211301). We also thank Xiaopeng Chen for his helpful comments.
