Experimental effect of wind and heavy rain on increased splash erosion using rainfall simulator

To investigate the erosion process that occurs, rainfall simulation is used with a model scale for natural rain events in laboratory conditions. The calculation of erosion and any soil erosion with a slope setting of 5% was carried out experimentally on a laboratory scale using a rain simulator and adding wind using a 2-inch snail blower. Experiments carried out in the laboratory included erosion tests driven by rain and erosion tests by rain, which were given additional wind variables. Rain intensity used for testing is using discharge 1 litre/minute,1.5 litre/minute, and 2 litre/minute as a representative variation of rainfall. The occurrence of rain and wind simultaneously within a certain period will cause greater loss of soil. Although many studies have been conducted on the effects of rain and the combined effects of wind on soil erosion, only a limited number of studies have focused on the combination of the two variables that occur together. The results showed that in the applied rain intensity and wind factor, the collision of the kinetic energy of the rain driven by the wind resulted in higher erosion when compared to that without the influence of the wind.


Introduction
The development of wind erosion control systems on cultivated land has been a process of developing experience from trial and error over many years by farmers to determine the best practices to control this problem [1].Not only does wind cause erosion, but soil also takes part as a variable of erosion.Soil is discussed comprehensively as The essential resource for human security (including climate and food security) in the 21 st century, with the main threat to soils being soil erosion by wind and water ever since humankind started with agriculture [2].Soil erosion during rainfall is a complex phenomenon resulting from detachment by raindrop impact and overland flow [3].Detachment of soil particles by the process of splash from rainfall is influenced by soil cohesion, soil aggregate properties such as OM (Organic Matters) and clay contents and erosivity of the rainfall [4].The determination of values for both parameters is, therefore, of paramount importance for runoff and erosion prediction purposes.Rainstorm intensity can be measured directly with a rain gauge connected to a data logger.Rainstorm kinetic energy, as a function of the mass and terminal velocity of raindrops, is more difficult to determine [5], [6] emphasized the importance of wind speed on drop velocity and rainstorm kinetic energy.Most studies have based rainstorm kinetic energy values on the terminal velocity of vertically falling drops without incorporating the effect of wind speed on the drop velocity.Only a few studies have dealt with the relationships between rainstorm intensity, wind velocity, and rainstorm energy [7], 1311 (2024) 012070 IOP Publishing doi:10.1088/1755-1315/1311/1/012070 2 [8], [9], [10].Based on the results of this research, we experimented by taking into account the relationship between wind and the erosivity of rain.

Materials and Methods
In this experiment, several tools and materials were used as experiments.Details of the tools used can be seen in the Materials section.

Material
Experiments were carried out at the Hydrology Laboratory, Department of Water Engineering, Universitas Brawijaya, Malang, Indonesia.Experiments to simulate rain, using a rainfall simulator with the Armfield Hydraulics S12-MKII-306 Hydrology type (Figure 1. Panel (A)) and 2 (two) NRT-PRO snail blowers to simulate the direction and strength of the wind (Figure 1. Panel (B)).The soil material used in the rainfall simulator uses 2 (two) types of soil with sand texture characteristics (Homogen sand) and mixed soil textures obtained from direct collection from the upstream Brantas watershed at the location of Junrejo Village, Batu City, Malang, Indonesia.

Design of Rainfall Simulator Setup
This research using a rainfall simulator was carried out in several stages, namely as follows: 1. Tool Calibration is a stage to match the tool's reading parameters before the tool is used.2. Prepare a rainfall simulator and water reservoirs needed when running with a rainfall simulator.3. Prepare and insert soil media into the rainfall simulator with the conditions given, among others: soil thickness of 7 cm in the rainfall simulator by manual compaction (applies to mixed soil and soil with a sand texture), the position of the soil is levelled evenly with the same soil density, the soil is in a dry condition, and the soil is conditioned to have passed the water content and void tests ratio.4. Prepare the blower and anemometer with the following usage plan: a.The blower was set to full opening and then recorded for constant wind speed at a height of 20 cm from the pan rainfall simulator b.The anemometer is set to measure wind speed and temperature.The anemometer, placed against the direction of the air released by the blower, then records the wind speed conditions with a logger until the wind conditions are stable.5.For the rainfall simulator nozzle openings, settings are given at 1 litre/minute, 1.5 litres/minute, and 2 litres/minute.This discharge is input for rainfall intensity scenarios; setting of discharge 1 litre/minute is representative of a rainfall height of 30 mm; 1,5 litre/minute is representative of a rainfall height of 45 mm; 2 litre/minute is representative of a rainfall height of 60 mm.In the initial stage, treatment was given without using wind (both for sand-textured soil and mixed-textured soil), and the experiment was repeated seven times to get an average number of erosion.For repetitions, it used the same condition of the soil and checked with an infiltrometer to make sure of the condition.The next stage is that the wind variable is given with the wind position to the right of the rainfall simulator installed parallel to it.This experiment is repeated seven times.The position and setup of the rainfall simulator while using the wind factor can be seen in Figure 3. Rainfall modeling utilized the S12 -Advanced Environmental Hydrology System Rainfall Simulator instrument [11], [12].The utilized slope gradients were 9% and 15%.The type of soil utilized in this research was taken from Sumber Brantas Village of Bumiaji Sub-District, City of Batu.The soil of the agricultural land of this location was then utilized as the medium to conduct modelling.To find out the type of soil at the location, analysis of soil type weight, calculation of grain distribution, sieve analysis, and hydrometer analysis [13] were conducted at the Water and Groundwater Laboratory of the Department of Water Resources Engineering at the Faculty of Engineering of Universitas Brawijaya.

Calculation Erosion
Wischmeier, et.al.[14] give the formula to calculate and predict the soil loss that is familiar, called the USLE method.The following equation is used: where: A = Amount of soil loss per unit area.Expressed in the units selected for K and the period selected for R (t/ha); R = The rainfall and the runoff factor is the number of rainfall erosion index (mm/hr); K = Soil erodibility factor (t.ha.hr/ha.MJ.mm);L = Slope-length factor; S = Slope-steepness factor; C = Land management factor; P = The ratio of soil loss with a support practice like contouring, strip cropping, or terracing.Wischmeier, et.al.[15] also, give a detailed explanation of R, R can be calculated using EI30 Bols (1978) in [16] proposes a formula for calculating the R factor on Indonesia in a model: 2.5 2 100(0.073+0.73)(2) where: R = Rainfall and the runoff factor based on rainfall erosivitiy (mm/hr); P = Annual precipitation in millimetres and R is in Mjmmha -1 hr -1 yr -1 .

Result and Discussion
The results of experiments carried out using a rainfall simulator can be seen in Fig. 4 -Fig.9. Figures 4 -6 show the average result of rain becoming runoff on mixed soil without adding the wind factor and using the wind factor.The red line represents the average rain runoff with rain intensities of 1, 1.5, and 2 litres/minute and is added to the wind factor from the right side of the rainfall simulator.Figures 7 -9 are the result of rain becoming runoff for soil with a sand texture using the same setup as using mixed soil.Based on the experimental pattern that has been carried out, the tendency to increase runoff occurs due to the addition of the wind factor.The increase of contour can not be seen very significantly at low rain intensity scales, whereas at high rain intensity scales, the increase of erosion contour in the rain to runoff is immediately visible physically.
To compare conditions in the pan rainfall simulator, contour identification is also used, which is formed from surface runoff that has occurred and is calculated using a grid for each area formed by surface flow from the rainfall simulation.The results of the calculations and the approach method used to see the contours formed, see Figure 10 for soil with a mixed soil type and Figure 11 for soil with a sand texture.10 is an approach to calculating erosion based on the contour area given by the rainfall intensity.In Figure 10, the soil used is mixed.The conditions given are to provide rain with an intensity of 1 -2 millimetres, then photos are taken and then transformed into a grid digitally using the same scale (1:1 scale).Adding the wind factor also uses the same method.
For soil that uses a sand texture type, it can be seen in Figure 11.The erosion approach method based on spatial analysis still uses the same experimental flow with mixed soil materials.In Figure 11, if we compare with Figure 10, the conditions obtained using sandy soil produce a wider and deeper erosion area.The average conversion results obtained in this experiment are shown in Table 1 for various soil conditions and additional wind factors.
In Table 1, the average results of the experiment show that soil with a sand texture has a wider area.If this is converted into an eroded area, the result is that the soil texture with a sand texture added with the wind factor gives a higher erosion value.
For a comparison of the values that have been obtained, it can be seen in Figure 12. Figure 12 shows the trend that the composition of the soil with a sand texture and the added wind factor gives a very significant value.

Figure 12. Comparison Of Grid Area Conversion Values Into Erosion Values For Various Scenarios And Intensities
In this experiment, the relationship value between intensity and surface runoff was also sought.Based on statistical results (can be seen in Figure 13), the relationship between rain intensity and surface runoff has a very strong relationship with an R 2 value of 0.909.After obtaining several results in the form of surface runoff values, the relationship between rain intensity and surface runoff, and the conversion of area to erosion.Using equation 1, the erosion value is searched using the USLE equation.Calculations for EI30 are presented in Table 2.Meanwhile, direct calculations are presented in Table 3.After obtaining the results using the values obtained using the empirical formula in equation 1, an analysis of the output (soil transported at the rainfall simulator outlet) is also carried out, and then the soil is converted into actual erosion values that occur as seen in Table 4.After obtaining the results from various scenarios and models, comparisons were made with the four erosion results obtained.The results obtained can be seen in Table 5.Then, the calibration of the relative error for erosion was obtained based on the empirical formula with area erosion, then erosion using the empirical formula with erosion obtained from the outlet rainfall simulator.

Conclusions
The results of this experiment conclude that the erosion value obtained based on area will provide quite a large value when compared with the erosion value using actual conditions.The combination of high-intensity rain, soil texture conditions, and added wind factors will result in a significant increase in erosion on land.If the three factors above are approached, the values obtained will provide an overestimated approach, but this can be reduced by calibrating the erosion conditions that occur in the field.The impact of wind factors should be investigated in the future regarding of anomaly in climatology trends.

Figure 2 .Figure 3 .
Figure 2. Location of mixed soil textures obtained from the upstream Brantas

Figure 10 .
Figure 10.Grid approach to defining erosion area using mixed soil caused by rainfall Panel (A) is the upper zone in the rainfall simulator; Panel (B) is the middle zone; Panel (C) is the downstream zone

Figure
Figure10is an approach to calculating erosion based on the contour area given by the rainfall intensity.In Figure10, the soil used is mixed.The conditions given are to provide rain with an intensity of 1 -2 millimetres, then photos are taken and then transformed into a grid digitally using the same scale (1:1 scale).Adding the wind factor also uses the same method.For soil that uses a sand texture type, it can be seen in Figure11.The erosion approach method based on spatial analysis still uses the same experimental flow with mixed soil materials.In Figure11, if we compare with Figure10, the conditions obtained using sandy soil produce a wider and deeper erosion area.The average conversion results obtained in this experiment are shown in Table1for various soil conditions and additional wind factors.In Table1, the average results of the experiment show that soil with a sand texture has a wider area.If this is converted into an eroded area, the result is that the soil texture with a sand texture added with the wind factor gives a higher erosion value.For a comparison of the values that have been obtained, it can be seen in Figure12.Figure12shows the trend that the composition of the soil with a sand texture and the added wind factor gives a very significant value.

Figure 11 .
Figure 11.Grid approach to defining erosion area using sand caused by rainfall Panel (A) is the upper zone in the rainfall simulator; Panel (B) is the middle zone; Panel (C) is the downstream zone

Figure 13 .
Figure 13.Relationship between Rain Intensity and Runoff Discharge

Table 1 .
Convert erosion calculations to the grid

Table 2 .
Results of calculating the rain erosivity index with several rain intensities

Table 3 .
Recapitulation of Erosion Rate Calculation Results using the USLE Method

Table 4 .
Rainfall Simulator Erosion Results and Conversion

Table 5 .
Comparison of erosion rate calculations