روح الله رضایی ارشد

Introduction: Under natural conditions, intensive and erosive storms commonly associate with high-speed winds. In fact, wind velocity affects water erosion rate through enforcing falling drops and enhancing rainfall erosivity. Therefore, knowledge of interaction between wind and rain as erosive agents on interrill erosion is of prime importance. However, no comprehensive study has been done on this topic under controlled laboratory conditions. This study was conducted to investigate interrill erosion affected by different rain intensities and wind velocities on several soils with different aggregate size distributions using the Simultaneous Wind-Rainfall-Runoff Simulator (SWRRS). For this purpose, a multisystem was constructed for the first time in Iran to investigate the simultaneous effects of wind and rain erosivity agents on soil erosion under laboratory conditions. Materials and Methods: The simulator was calibrated in two cases. First, the intensity and uniformity of the simulated rains were assessed for each nozzle, separately. Second, the calibration procedure was performed for different combinations of the selected nozzles to achieve the best performance. For each case, different water pressures were generated to introduce several water discharges and make initial raindrop velocities. Afterwards, the interrill erosion experiment was done using four constant wind speeds including 0, 6, 9 and 12 m s-1at the height of 40 cm which were applied in combination with three rain intensities of 30, 50 and 75 mm h-1 on three soil samples with different aggregate size distributions (D2mm, D4.75mm and D8mm). Each treatment was conducted at three replicates under laboratory controlled conditions. By using different wind speeds, rain intensities and soil aggregate sizes, interrill erosion rate was measured under steady state conditions. Results and Discussion: Results showed that wind velocity has a significant effect on interrill erosion rate and the interaction between wind and rain on interrill erosion was significant, as well. Although, there was no significant difference between the erosion rate at wind velocity of 0 and 6 m s-1, the wind velocity of 9 and 12 m s-1 showed significant difference with and higher erosion rates than the velocity of 6 m s-1. The mean erosion rate at wind velocities of 0, 6, 9, 12 m s-1 was 0.43 × 10-4, 0.54 × 10-4, 0.97 × 10-4 and 1.46 × 10-4 kg m-2 s-1, respectively. With increasing rain intensity from 30 to 75 mm h-1, the erosion rate increased from 0.52 × 10-4 to 1.16 × 10-4 kg m-2 s-1. On average, the erosion rate of the soil containing larges aggregates i.e. D8mm (0.73 × 10-4 kg m-2 s-1) was less than that with the finest aggregates i.e. D2mm (0.99 × 10-4 kg m-2 s-1). The findings of this study highlighted the importance and necessity of more attention to wind speed particularly those velocities faster than a threshold velocity in the study of interrill erosion. Conclusion: In arid and semi-arid regions such as most parts of Iran, rainstorms are usually accompanied by strong winds. Despite the undeniable influence of wind on the erosive power of rain, a host of research has investigated water and wind erosion processes, separately. Therefore, this study was done to investigate the simultaneous effect of wind velocity and rain intensity on interrill erosion rate in three soil samples. The results indicated that wind velocity has a remarkable influence on interrill erosion rate due to wind-driven rain. Wind velocities faster than 6 m s-1 increased interrill soil erosion rate, particularly those combined with higher rain intensities. This is due to an increase in the velocity of falling raindrops on the soil surface which results in greater kinetic energy. Also, the findings showed that the soil containing coarser aggregates due to greater random roughness exhibited less sensitivity and interrill erosion rates as compared with the soil having finer aggregates, especially at faster wind velocities. The rate of interrill erosion in soil D2mm was 1.35 times higher than soil D8mm indicating the importance of random roughness. In addition, there was no significant difference between the measured erosion rates at wind speeds of 0 and 6 m s-1, in all cases. However, with increasing wind speed from 6 to 9 and also to 12 m s-1, significant increases in soil erosion rates were observed. Accordingly, a threshold wind velocity can be considered in wind-driven interrill erosion. The findings of the present study can be applied for better understanding and modeling of water and wind erosion mechanisms and dominant processes.

Many natural rainstorms are accompanied by wind blowing. However, so far no comprehensive research has been reported on the influence of wind on rain-induced erosion under laboratory conditions in Iran. The present study was conducted to investigate the interactive effects of different wind velocities and rain intensities on flow hydraulic parameters and on interrill erosion rate of several agricultural soils. For this purpose, a simultaneous wind, rain and runoff simulator was used, which has been designed and constructed for the first time in the country.
Various combinations of four wind speeds including 0, 6, 9 and 12 m s-1, three rain intensities of 30, 50 and 75 mm h-1 were introduced on three cropland soils with different aggregate size distributions with the largest particle size of 2, 4.75, and 8 mm, each at three replications. Different flow hydraulic parameters including mean flow velocity, flow depth, shear stress, stream power and unit stream power and also the rate of interrill erosion were measured. Afterwards, the effects of wind velocity on the flow hydraulic parameters and also the influence of these parameters on interrill erosion rate were assessed.
The results showed that depending on the wind velocity, the rate of interrill erosion varied from 0.021 and 0.22 g m-2 s-1. In this research, the wind velocity of 6 m s-1 was introduced as a threshold value. With increasing wind speed particularly those speeds higher than the threshold, the flow parameters of velocity and unit stream power increased, whereas, flow depth and shear stress decreased. In addition, stream power increased as the wind speed increased up to the threshold wind velocity, and at the higher wind speeds, the reverse trend was observed. The result indicated that wind speed can control interrill erosion rate by affecting on flow hydraulic parameters. Interrill erosion increased with increasing velocity and unit stream power of the flow, while it was reduced when flow depth, shear stress and stream power increased, this was attributed to the expenditure of raindrops energy for passing through water depth. In fact, the opposite relationship between flow velocity and water depth affects the other hydraulic parameters. Moreover, the presence of coarser aggregates at the soil surface increased water depth and decreased the velocity and unit stream power of flow, resulting in reduced interrill erosion.
The findings of this study showed that in wind-driven rains particularly at those wind speeds higher than 6 m s-1, interrill erosion rate is intensified because of increasing in rain erosivity and flow velocity and decreasing in flow depth. It was found that with appropriate soil management in agricultural lands for increasing the size and strength of surface aggregates, flow velocity and consequently soil erosion can be reduced. From another point of view, the presence of stable and coarser aggregates at soil surface decreases interril erosion. Overall, the findings of this research revealed the importance and necessity of more studies on soil erosion processes due to wind-driven rain.

Direct measurement of soil hydraulic characteristics is costly and time-consuming. Also، the method is partly unreliable due to soil heterogeneity and laboratory errors. Instead، soil hydraulic characteristics can be predicted using readily available data such as soil texture and bulk density using pedotransfer functions (PTFs). Artificial neural networks (ANNs) and statistical regression are two methods which are used to develop PTFs. In this study، the multi-layer perceptron (MLP) neural network and backward and stepwise regression models were used to estimate saturated hydraulic conductivity using some soil characteristics including the percentage of particle size distribution، porosity، and bulk density. Data of 125 soil profiles were collected from the reports of basic soil science and land reclamation studies conducted by Khuzestan Water and Power Organization. The results showed that MLP neural network having Bayesian training algorithm with the greater coefficient of determination (R2=0. 65) and the lower error (RMSE =0. 04) had better performance than multiple linear regression model in predicting saturated hydraulic conductivity.