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

Mohamed A. M. Abd Elbasit1,2, Hiroshi Yasuda1, Atte Salmi3 and Zahoor Ahmad1 *1Arid Land Research Center, Tottori University, Tottori 2Desertification Research Institute, National Center for Research, Khartoum 3Vaisala Oyj, Helsinki, 1Japan 2Sudan 3Finland* 

#### **1. Introduction**

166 Soil Erosion Studies

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Rainfall represents the major driver of soil detachment in erosion processes. The potential of rainfall to detach soil has been defined as rainfall erosivity. The relationship between rainfall intensity and rainfall drop size distribution (DSD) controls various rainfall characteristics including the rainfall erosivity (Abd Elbasit et al., 2010). The relationship between rainfall intensity and rainfall erosivity differs due to geographical location under natural rainfall (Hudson 1965; Wischmeier and Smith, 1978; Zanchi and Torri, 1980; Van Dijk et al., 2002) and due to type and configuration of rainfall simulators under simulated rainfall (Hall, 1970; Olayemi and Yadav, 1983; Auerswald et al., 1992; Salles and Poesen, 2000). The role of rainfall microstructure on the determination of rainfall erosivity has attracted several researchers in the past. However, our understanding on this subject is still limited due to the lack of equipments that are able to measure the rainfall drop parameters and ultimately the rainfall kinetic energy. Several indices have been suggested to quantify the rainfall erosivity (Abd Elbasit et al., 2010). Generally, the suitable erosivity index must include the drop mass and velocity as major variables for raindrop power determination. The erosivity index has been described by Epema and Riezebos, 1983 as follows:

$$E \propto m^a \ v^\beta \tag{1}$$

where *m* is drop mass in (kg); *v* is fall-velocity (m s-1); α and β are coefficients.

The most used indices are raindrop kinetic energy (KE) and momentum (M). In the KE and M the α is equal to one where the β is equal to two in KE and one in M. In general, the raindrop fall velocity can be related to drop size by a power relationship. Accordingly, the raindrop size distribution affect both constituents of rainfall erosivity. Thus, theoretically the rainfall DSD (or rainfall micro-structure) has a great impact on rainfall erosivity. In this study, the impact of rainfall microstructure on rainfall erosivity and splash soil erosion

Impact of Rainfall Microstructure on Erosivity and Splash Soil Erosion Under Simulated Rainfall 169

optical methods have, also been utilized, where raindrop size and velocity are monitored simultaneously and then the erosivity indices are calculated directly from these two parameters (Salles and Poesen, 2000; Nanko et al., 2004). The raindrop erosivity can be evaluated from the rainfall DSD measured by different methods (continuous, disdrometers or non-continuous, filter paper and flour-pellet) and use of drop fall velocity values derived

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.

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

from empirical and physical relationships.

**1.4 Dripper-type rainfall simulators** 

(Abd Elbasit et al., 2010).

**1.3 Rainfall simulation** 

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 size distribution have been measured using piezoelectric sensor.

#### **1.1 Rainfall erosivity evaluation**

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 calculated as follow:

$$R-factor = \frac{1}{n} \sum\_{i=1}^{n} \left[ \sum\_{k=1}^{m} KE\left(I\_{50}\right)\_k \right] \tag{2}$$

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 dominant type of rainfall. For example:

$$KE = (11.89 + 8.73\log\_{10} I) \times I \tag{2a}$$

(Wischmeier and Smith, 1958), USA

$$KE = \text{29.86}(I - 4.29) \tag{2b}$$

(Hudson, 1965), Zimbabwe

$$KE = 36.8I(1 - 0.691e^{-0.038I})\tag{2c}$$

(Jayawardena and Rezaur, 2000a), Hong Kong

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

Determination of the I-KE relationships under certain geographical location or simulated rainfall requires information about the rainfall KE or at least the rainfall DSD.

#### **1.2 Raindrop erosivity evaluation**

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, optical methods have, also been utilized, where raindrop size and velocity are monitored simultaneously and then the erosivity indices are calculated directly from these two parameters (Salles and Poesen, 2000; Nanko et al., 2004). The raindrop erosivity can be evaluated from the rainfall DSD measured by different methods (continuous, disdrometers or non-continuous, filter paper and flour-pellet) and use of drop fall velocity values derived from empirical and physical relationships.
