**1.3 Rainfall simulation**

168 Soil Erosion Studies

under simulated rainfall condition will be discussed. A dripper-type rainfall simulator located at the Arid Land Research Center, Tottori University, Japan has been used to simulate events with rainfall intensity ranged between 10 to 30 mm h-1. The splash soil erosion has been evaluated using splash cup method. The rainfall kinetic energy and drop

R- factor in the Universal Soil Loss Equation (USLE) and its revised and modified versions represents the major rainfall erosivity, which can be defined as the product of total kinetic energy of storm times its 30 min maximum intensity(EI30) and annual average can be

> 1 1 1 *n m*

R-factor is average annual rainfall and runoff erosivity (MJ mm ha-1 h-1 year-1); KE is total kinetic energy of single storm (MJ ha-1); I30 is the maximum 30 min rainfall intensity (mm h-1); m is the number of k erosive storms in each j year; n is the number of years used to obtain average R (Renard and Freimund, 1994). Several I-KE relationships can be applied in order to determine the storm kinetic energy depending on the geographical location and

Determination of the I-KE relationships under certain geographical location or simulated

Rainfall drop size distribution (DSD) represents the primary rainfall data that can be used in order to quantify the rainfall erosivity. However, devices for continuous determination of the KE and DSD during rainfall event have been used in few meteorological stations. For this reason, several indices have been suggested to estimate the rainfall erosivity from common rainfall parameters (rainfall macro-structure), such as daily, and monthly rainfall data. Raindrop erosivity can be determine directly by using piezoelectric transducer where the measured water drop kinetic energy or momentum related with output voltage from the transducer due to the drop impact (Madden et al., 1998; Jayawardena and Rezaur, 2000b; Abd Elbasit et al., 2007; Abd Elbasit et al., 2010; Abd Elbasit et al., 2011). Anologously,

*R factor KE I n* 

*i k j*

*k*

<sup>10</sup> *KE* (11.89 8.73lo g *I I* ) (2a)

*KE I* 29.86( 4.29) (2b)

0.038 36.8 (1 0.691 )*<sup>I</sup> KE I e* (2c)

(2)

size distribution have been measured using piezoelectric sensor.

<sup>30</sup>

**1.1 Rainfall erosivity evaluation** 

dominant type of rainfall. For example:

(Wischmeier and Smith, 1958), USA

**1.2 Raindrop erosivity evaluation** 

(Jayawardena and Rezaur, 2000a), Hong Kong

where KE is rainfall time-specific kinetic energy (KEtime) in J m-2 h-1.

rainfall requires information about the rainfall KE or at least the rainfall DSD.

(Hudson, 1965), Zimbabwe

calculated as follow:

Rainfall simulators are developed to mimic natural rainfall in its different characteristics. The rainfall properties including rainfall intensity and energy are the important parameters for determining the rainfall erosivity. Generally, rainfall simulators can be divided in two categories: single drop simulators (SDS) and multiple drop simulators (MDS). The SDS have been used intensively to investigate the splash erosion processes (e.g. Al-Durrah and Bradford, 1982; Cruse and Francis, 1984; Gantzer et al., 1985; Nearing and Bradford, 1985; Bradford et al., 1986; Nearing et al., 1986; Sharma and Gupta, 1989; Mouzai and Bouhadef, 2003; Furbish et al., 2007). Although these studies have improved our understanding for splash soil erosion, they fail to extrapolate these results to natural field condition (Abd Elbasit et al., 2010). The MDS produced range of raindrops similar to that found under natural rainfall. However, the big challenge for these simulators is to generate rainfall similar to natural rainfall or at least with I-KE trend similar to natural rainfall. The MDS can be categorized into three main groups: the drip-screen type (dripper type, dripolator), vertical spray type or nozzle-type and sprinkler or rotating spray-types. In this study, a dripper-type rainfall simulator has been used to simulate rainfall with different intensities.

## **1.4 Dripper-type rainfall simulators**

A dripper type rainfall simulator located at the Arid Land Research Center, Tottori University, Japan was used to simulate rainfall with intensities ranging between 10 to 30 mm h-1 (Figure 1). The simulator is 12 m in height, which is theoretically enough for most of the drop sizes to reach their terminal velocity (Wang and Pruppacher, 1977) experimental results. The simulator consisted of a main steel frame, a dripper system, a positive displacement pump, a set of solenoid water valves to control water flow, and a computerized control system for various operations. The height of the main frame was 12.5 m and the dripper system was fixed on the top of this frame (Figure 1). The dripper system consisted of 16 disc-type water distributors attached to a horizontal steel frame (2.55 x 1.5 m) in six rows (Abd Elbasit et al., 2010). Each distributor had 45 tubes with inner and outer diameters of 2 and 3.5 mm respectively and at the end of each tube, a flat cut hypodermic needle was fixed (Figure 1). The inner and outer diameter of the needles was 0.4 and 0.6 mm respectively. The other end of the needle was attached to a metallic plate in such a way that the needle protruded 2.6 cm (Abd Elbasit et al., 2010). There were 18 metallic plates in total and each plate had two rows of needles. The distance between the rows was 6 cm, and the needles were arranged in 6 cm offset pattern with a needle to needle distance of 6 cm within the row. Under the needles, an oscillating screen was fixed in order to distribute the rainfall evenly, improve the drop size distribution and to prevent continuous water flow (Figure 3). The oscillating screen (2.35 x 1.33 m) consisted of two sheets of metallic mesh (10 mm) moving horizontally and in opposite directions of each other, driven by an electric motor (Abd Elbasit et al., 2010).

Impact of Rainfall Microstructure on Erosivity and Splash Soil Erosion Under Simulated Rainfall 171

Fig. 2. Schematic view for the piezoelectric kinetic energy and drop size distribution sensors

The sensor is constructed from a piezoelectric detector covered by stainless steel shell (Figure 2). The voltage pulses delivered by the piezoelectric element are filtered, amplified, digitized, and finally analyzed as to their selected parameters related to the raindrop size. Final computations are performed by the micro-processor system (Abd Elbasit et al., 2010). The DSD sensor was calibrated at Vaisala Rain Laboratory; Finland using controlled drop sizes falling from a height of 14 m and the velocity of each drop size was measured using two parallel laser beams and a prism. The received optical signal was converted to a voltage signal, which was proportional to the area of the laser beam intercepted by the raindrops (Salmi and Elomaa, 2007). The sensor was compared with a Joss-Waldvogel RD-69 disdrometer under natural rainfall conditions in Finland (Pohjola et al., 2008) and the results of the two methods showed significant agreement for raindrop size greater than 0.80 mm. The KE sensor was calibrated using rain drops with known kinetic energy values. The simulator and optical method used for the DSD sensor calibration were also used to calibrate the KE sensor. The raindrops' KE that was used for the KE sensor calibration was calculated from the raindrop size (controlled by the rainfall simulator) and fall velocity (measured using the optical method). The KE sensor was also validated under simulated rainfall and the sensor output (direct KE measurement) was compared with the calculated KE using rainfall DSD and empirically calculated velocity from drop size. The correlation between directly measured KE using the KE sensor and estimated KE was statistically highly significant under different rainfall intensities and empirical relationships (Abd Elbasit et al., 2007, Abd Elbasit et al., 2011). Moreover, there was agreement between the two methods in terms of the shape of the relationship between rainfall intensity and measured and estimated KE. The signals from the two sensors were logged in two notebook computers using the RS-232 serial interface and data logging software. The rainfall intensity was measured using a tipping-bucket rain gauge (Davis rain collector II, CA, USA) with 0.2 mm resolution. The rain gauge was attached to event data logger (HOBO Event Logger;

Onset Computer Corp., MA, USA) with 0.5 s interval recording accuracy.

The splash measurement was repeated three times for each rainfall intensity level. In each study three splash cups were used. The mean value for each intensity was used for

**2.2 Measurement of splash soil erosion** 

modified from Vaisala WXT510® sensor.

Fig. 1. Dripper-type rainfall simulator. (a) main frame, (b) dripper system, and (c) disc-type water distributor

The water pump used to supply water to the dripper system of the rainfall simulator was a positive displacement type. The water flow rate was controlled by adjusting the rotational speed of the pump (Abd Elbasit et al., 2010). The rainfall simulator was equipped with four 1 m3 water tanks and the water flow in and out these tanks was controlled by the solenoid water valves. A high-performance water filtering system was connected to the water supply flowing to the tanks to avoid needle clogging. A computer system controlled the solenoid water valves, pump rotational speed, and oscillating screen. Before using the rainfall simulator for experiments, a priming system was used to remove all the air from the pipe system. The rainfall simulator was calibrated for the rainfall spatial distribution on the experimental area (2.1 x 1.1 m), and to determine the relationship between the flow rate and rainfall intensity (Abd Elbasit et al., 2008). In the experimental area, a table was placed at a height of 0.5 m on which the soil was placed when the splash experiment was conducted. The rainfall simulator was able to simulate rainfall intensities ranging from 1.0-200 mm h-1.

#### **2. Materials and methods**

#### **2.1 Application of piezoelectric transducer in erosivity quantification**

The rainfall erosivity was measured using two piezoelectric sensors, one to measure the kinetic energy (KE, mJ) and the other to measure drop size distribution (DSD, mm), at 10 second interval. The both sensors were modified from the piezoelectric Vaisala RAINCAP® rain sensor. The measurement principle of the sensor is based on the acoustic detection of individual raindrop impact (Salmi and Ikonen, 2005). The drop impact generates acoustic waves to the piezoelectric detector (Figure 2). Resulting mechanical stresses in the piezoelectric material causes a voltage between the sensor electrodes. Due to the well known dependence between terminal velocity and mass of the drop, the drop size can be determined from the voltage signal (Abd Elbasit et al., 2010).

Fig. 1. Dripper-type rainfall simulator. (a) main frame, (b) dripper system, and (c) disc-type

The water pump used to supply water to the dripper system of the rainfall simulator was a positive displacement type. The water flow rate was controlled by adjusting the rotational speed of the pump (Abd Elbasit et al., 2010). The rainfall simulator was equipped with four 1 m3 water tanks and the water flow in and out these tanks was controlled by the solenoid water valves. A high-performance water filtering system was connected to the water supply flowing to the tanks to avoid needle clogging. A computer system controlled the solenoid water valves, pump rotational speed, and oscillating screen. Before using the rainfall simulator for experiments, a priming system was used to remove all the air from the pipe system. The rainfall simulator was calibrated for the rainfall spatial distribution on the experimental area (2.1 x 1.1 m), and to determine the relationship between the flow rate and rainfall intensity (Abd Elbasit et al., 2008). In the experimental area, a table was placed at a height of 0.5 m on which the soil was placed when the splash experiment was conducted. The rainfall simulator was able to simulate rainfall intensities ranging from 1.0-200 mm h-1.

The rainfall erosivity was measured using two piezoelectric sensors, one to measure the kinetic energy (KE, mJ) and the other to measure drop size distribution (DSD, mm), at 10 second interval. The both sensors were modified from the piezoelectric Vaisala RAINCAP® rain sensor. The measurement principle of the sensor is based on the acoustic detection of individual raindrop impact (Salmi and Ikonen, 2005). The drop impact generates acoustic waves to the piezoelectric detector (Figure 2). Resulting mechanical stresses in the piezoelectric material causes a voltage between the sensor electrodes. Due to the well known dependence between terminal velocity and mass of the drop, the drop size can be

**2.1 Application of piezoelectric transducer in erosivity quantification** 

determined from the voltage signal (Abd Elbasit et al., 2010).

water distributor

**2. Materials and methods** 

Fig. 2. Schematic view for the piezoelectric kinetic energy and drop size distribution sensors modified from Vaisala WXT510® sensor.

The sensor is constructed from a piezoelectric detector covered by stainless steel shell (Figure 2). The voltage pulses delivered by the piezoelectric element are filtered, amplified, digitized, and finally analyzed as to their selected parameters related to the raindrop size. Final computations are performed by the micro-processor system (Abd Elbasit et al., 2010). The DSD sensor was calibrated at Vaisala Rain Laboratory; Finland using controlled drop sizes falling from a height of 14 m and the velocity of each drop size was measured using two parallel laser beams and a prism. The received optical signal was converted to a voltage signal, which was proportional to the area of the laser beam intercepted by the raindrops (Salmi and Elomaa, 2007). The sensor was compared with a Joss-Waldvogel RD-69 disdrometer under natural rainfall conditions in Finland (Pohjola et al., 2008) and the results of the two methods showed significant agreement for raindrop size greater than 0.80 mm. The KE sensor was calibrated using rain drops with known kinetic energy values. The simulator and optical method used for the DSD sensor calibration were also used to calibrate the KE sensor. The raindrops' KE that was used for the KE sensor calibration was calculated from the raindrop size (controlled by the rainfall simulator) and fall velocity (measured using the optical method). The KE sensor was also validated under simulated rainfall and the sensor output (direct KE measurement) was compared with the calculated KE using rainfall DSD and empirically calculated velocity from drop size. The correlation between directly measured KE using the KE sensor and estimated KE was statistically highly significant under different rainfall intensities and empirical relationships (Abd Elbasit et al., 2007, Abd Elbasit et al., 2011). Moreover, there was agreement between the two methods in terms of the shape of the relationship between rainfall intensity and measured and estimated KE. The signals from the two sensors were logged in two notebook computers using the RS-232 serial interface and data logging software. The rainfall intensity was measured using a tipping-bucket rain gauge (Davis rain collector II, CA, USA) with 0.2 mm resolution. The rain gauge was attached to event data logger (HOBO Event Logger; Onset Computer Corp., MA, USA) with 0.5 s interval recording accuracy.

#### **2.2 Measurement of splash soil erosion**

The splash measurement was repeated three times for each rainfall intensity level. In each study three splash cups were used. The mean value for each intensity was used for

Impact of Rainfall Microstructure on Erosivity and Splash Soil Erosion Under Simulated Rainfall 173

Fig. 4. Simulated rainfall drop size distribution under various rainfall intensities.

increasing the number of sampled intensities (Figure 7).

under various simulated rainfall intensities.

The KE pattern was highly different from drops number percentage as the KE resulted from large drops was very high compared to small drops classes. This can be attributed to two reasons: first, the drop mass increases exponentially with diameter; second the raindrop fall velocity has a non-linear relationship with drop diameter. The small drops number and KE percentage is shown in Figure 6. The small drops number and KE percentage showed relative agreement between each other. Both the drops number and KE percentage showed a decrease with rainfall intensities. The large drops number and KE percentage showed increasing pattern with the rainfall intensities. The large drops number percentage is approximately less than 30%, however, the KE produced by this percentage of raindrops was between 70 to 90%. These results emphasize that the large drops number percentage is a determination factor for rainfall KE. The correlation coefficient between the large drops number (%) and KE (%) was 0.78 and this correlation coefficient can be improved by

Fig. 5. Relationship between large drops number percentage and kinetic energy percentage

determining the impact of rainfall micro-structure on soil splash erosion. The splash-cups were prepared using PVC pipe-connectors with a diameter of 10 cm and height of 20 cm (Figure 3). At a height of 10 cm, a metal screen was fixed in the cup using silicon sealant (Abd Elbasit et al., 2010). A filter paper was placed on top of the screen and then the cup was filled up to the edge with silty clay loam soil collected from the Tohaku area, Tottori Prefecture, Japan. The fine sand, silt and clay percentage was 8.24, 61.78, and 29.98%, respectively.

Fig. 3. Schematic view of splash cup.

The soil was air dried in a glasshouse and then mechanically crushed and sieved through 2 mm mesh. Before starting the experiment, the soil was again dried in an oven at 105 ºC for 24 hours. The bulk density of the soil in the cup was 1.10 ± 0.01 g cm-3. The cups were then exposed to the simulated rainfall for different durations depending on the rainfall intensity to be tested. The rainfall duration ranged from 18 minutes for 10 mm h-1 rainfall intensity to 6 minutes for 30 mm h-1. The rainfall depth was kept constant at 3 mm to avoid any surface pond formation that would have reduced the rainfall energy striking the soil surface. The splash was measured by the difference in the total oven dry weight of each splash cup before and after exposure to simulated rainfall.
