development of mini portable pressure head type rainfall

Development of Mini Portable Pressure Head Type Rainfall Simulator

for Investigating Runoff, Infiltration and Sediment Discharge

JIRARATCHWARO Charoen*, SUZUKI Yutaka**, SAHO Norihide***,

ONWONA-AGYEMAN Siaw*** and WATANABE Hirozumi***

* United Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology, 3-5-8

Saiwaicho, Fuchu, Tokyo 183-8509, JAPAN.

** Faculty of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwaicho, Fuchu, Tokyo 183-

8509, JAPAN.

*** Institute of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwaicho, Fuchu, Tokyo 183-

8509, JAPAN.

Abstract

A Mini Portable Pressure Head (MPPH) type Rainfall Simulator was developed for investigating runoff, sediment

and infiltration from the soil in laboratory. The raindrops were produced from 175 pieces of 0.34 mm needles which

were embedded under the drop former. The uniformity coefficient of the simulated rainfall was 84.3%. The drop

velocity 5.2 m s-1 and kinetic energy was 0.263 J m-2 s-1 for rainfall intensity of 70 mm h-1.

The investigations of runoff, sediment discharge and infiltration were conducted using the Andosol soil with the

average dry bulk density of 0.58 × 103 kg m-3 and the volumetric moisture content at the field capacity of 0.39 cm3

cm-3. The simulation was set for the rainfall intensity of 70 mm h-1 on the lysimeter surface at 5% slope. The runoff

and infiltration samples were collected each 10 minutes during the experiment of 100 minutes.

The runoff occurred about 98 ± 44.5 seconds after the rainfall simulation started and rapidly increased to be 52 mm

h-1 while infiltration outflow occurred after 60 minutes with average flow of 17 mm h-1. The average sediment

concentration in discharge water was about 5.99 g L-1 and cumulative sediment discharge was about 3.81 t ha-1 h-1.

The developed rainfall simulator was able to produce useful datasets for runoff, infiltration and sediment discharge.

Key words : Rainfall simulator, Runoff, Infiltration, Sediment, Soil erosion, Andosol soil

1. INTRODUCTION

Rainfall simulator is a tool which has the ability to take

many measurements within a short time instead of

experiments under natural rain. Iserloh et al. (2012)

reported that rainfall simulators has been used as research

tools extensively for field and laboratory characterizations

of hydrogeomorphological studies including runoff,

infiltration and erosion characteristics as well as studies of

sediment and pollutant transport within watersheds. They

are also used for measuring impacts of revegetation,

consolidation, and protection of soil physical properties

and erodibility (Aksoy et al., 2012). Desirable features of

a portable rainfall simulator according to Iserloh et al.

(2012) are (I) Good mobility, (II) low water consumption,

(III) easy handling and control of test conditions, (IV)

homogeneous spatial rainfall distribution, and (V) easy

and fast training of operators to obtain reproducible

experiments.

Surface runoff is the water from rainfall, snowmelt or

other sources that flows over the land surface. It occurs

when soil moisture exceeds a soil’s infiltration capacity

and the excess rainfall turns into overland flow. Soil

particles transported by runoff water are referred to the

sediment and become a part of the erosion process. Soil

erosion is a worldwide problem and has become a major

global concern since it has severe impacts on agriculture

and the environment (Wudneh et al., 2014). Pimentel et al.

(1995) indicated that about 80% of the world’s agricultural

land suffers from moderate to severe soil erosion. Water

erosion was identified as the most important form of soil

degradation, followed by wind erosion (Oldeman et al.,

1991). The study of the soil erosion extents a wide range

of spatial scales including simple plots for scientific study,

the field scale of interest to the single farmer, the

catchment scale for community-level issues, and regional

and national scales for policy-maker decisions (Kirkby et

al., 1996).

Ⅰ_297

農業農村工学会論文集　IDRE Journal　No. 309 (87-2), pp.Ⅰ_297-Ⅰ_302 (2019.12) 〈Research Paper〉

The portable rainfall simulators normally use a pump for

suppling water (Iserloh et al., 2012, Yadav and Watanabe,

2018). The mini portable pressure head (MPPH) type

rainfall simulator is based on the hydraulic head pressure

principle to supply artificial rain instead of a pump. The

main advantage of this feature is that the device enables to

supply water without using electricity. Furthermore, it can

be used not only for indoor experiments, but also for

outdoor places even without electricity.

The objectives of this study were to develop and

calibrate the new type of rainfall simulator, and to apply

for investigating the runoff, infiltration and sediment

discharge under laboratory conditions.

2. MATERIALS AND METHODS

2.1 Pressure Head Rainfall Simulator

The advantage of laboratory investigations in

comparison with field measurements is the ability to

control the determining factors (e.g. erosivity, erodibility,

slope, roughness, soil moisture content) and to concentrate

research on specific processes to systematically fill

existing knowledge gaps (Iserloh et al., 2012). The MPPH

rainfall simulator having a variable pressure head unit was

used in this experiment (Fig. 1). Its other components

consist of the frame, drop former, needles and water supply

system. The catchment area of the experimental lysimeter

surface was 0.33 m by 0.48 m.

2.1.1 Frame and Accessories

The structural frame was made of aluminum with

dimensions of 0.57 m × 0.36 m at the base with 4 wheels,

and the adjustable height between 2.00 to 2.80 m. The

upper part of this frame has a water pressure head tank for

supplying constant water flow to the drop former. The

opposite side of the tank is the drop former which is made

of acrylic material with dimensions of 0.36 m × 0.51 m and

equipped with 175 pieces of needles. The needles had

inner diameter of 0.34 mm and outer diameter of 0.642 mm

and a spacing of needles was 3.0 cm. The top of this drop

former is connected to a piezometer for measuring the

pressure head inside the drop former.

2.1.2 Water Supply System

The MPPH rainfall simulator has a dual water supply

system. It works either by using a pump, or by directly

connecting with tap water to supply water to the drop

former. The supply system has an inlet valve on control

panel and flowmeter to control the amount of inflow and

releases excess flow to the drainage pipe. The water from

the flow meter is discharged to the pressure head tank,

which rests on top of the frame. In this pressure head tank,

the water head is constant and determined by the height of

the tank (26 cm high). Water in the tank passes through the

rubber tube which is connected from the bottom of

pressure head tank to the drop former. The amount of

inflow and pressure head inside the drop former is

controlled by the inlet valve. The pressure head inside drop

former was monitored by piezometer (Fig. 1).

2.1.3 Drop Size

Drop size is one of the most important key factors for

studying soil erosion. The drop size is related to rainfall

intensity and kinetic energy.

In order to determine the drop size emitted from the

needle for MPPH rainfall simulator, a 8 cm PET bottle

with a 0.34 mm needle embedded at the bottom was

prepared for calculation of the size of the raindrop. In this

experiment, the water level in the PET bottle for testing

was set at 10 cm high. After that, the number of drops and

the amount of water were measured for 2 minutes.

To calculate the drop size, we assumed that each drop

was spherical. Then the diameter of the drop from a needle

was calculated by using the relationship between density,

mass and volume as shown in the equation below:

where Ddrops is the drop diameter (cm), mdrop is the mass of

one drop (g) and ρw is the density of the water (kg m-3).

2.1.4 Drop Velocity

The MPPH rainfall simulator was set at a rainfall

intensity of 70 mm h-1. The distance between the tip of

needles and lysimeter surface was about 1.85 m. In this

study, falling velocity of a raindrop was determined

graphically by the relationship between raindrop

velocities, drop diameters and falling distances given by

van Boxel (1998). The terminal velocity of the drop

diameter of this experiment was also graphically obtained

from the figure between terminal velocity and raindrop

diameter plotted by van Boxel (1998).

(1)

Fig. 1 Diagram of MPPH rainfall simulator and water supply system

Ⅰ_298

農業農村工学会論文集　IDRE Journal　No.309(87-2), pp.Ⅰ_297-Ⅰ_302 (2019.12)

2.1.5 Kinetic Energy

The kinetic energy of rainfall simulator was calculated

per unit quantity of rain (ERA) (Kinnell, 1981). By

considering the rainfall intensity at 70 mm h-1, the kinetic

energy equation could be written in the form as below:

where ERA is kinetic energy (J m-2 s-1), ρ is density of water

(kg m-3), I is rainfall intensity (mm h-1) and v is impact

velocity of individual raindrop (m s-1).

2.1.6 Calibration of Rainfall Intensities and Uniformity

Coefficient

The MPPH rainfall simulator was calibrated for the

rainfall intensities by controlling the inlet valve. The water

pressure in the constant head tank has constant level, while

water pressure in drop former was adjusted by monitoring

the pressure head in piezometer which set up next to the

drop former. The calibration was performed by using 9 of

200 mL beakers placed 1.85 m below the drop former for

2 minutes. The rainfall intensities were calculated from the

amount of water collected.

The artificial rainfall that was produced by MPPH

rainfall simulator falls at the same position if there is no

disturbance. The natural rainfall, however, falls

heterogeneous over the catchment area. In this laboratory

experiment the falling raindrops from the drop former

were disturbed by wind from the two fans located about 50

cm away from the rainfall simulator and 1 m high with an

angle of 30 in the horizontal to produce randomized

falling positions of raindrops. Wind velocity measured by

anemometer (MT-EN1A, MOTHERTOOL CO., LTD,

Nagano, Japan) at the center of catchment area about 1.10

m above the lysimeter was 2.0 m s-1. The clogging needles

were replaced with new needles during the process of the

calibration before each experiment. The raindrops were

collected in 200 mL beakers placed 1.85 m below the drop

former for 2 minutes for 9 positions and 3 replications.

Amounts of raindrop water were measured for the

calculation of uniformity coefficient.

Kara et al. (2008) reported that a technical criterion such

as Christiansen uniformity coefficient can be used for the

selection of the adequate sprinkler and nozzle diameter for

the prevailing operation and environmental conditions at

the given location. The randomized distribution of

raindrop was determined by uniformity coefficient

developed by Christiansen (Kara et al., 2008) as equation

below:

where CU is Christiansen’s coefficient of uniformity (%),

z is the amount of water measured in each beaker (mL), m

= (Σz)/n is average amount of water (mL) and n is the

number of beakers collecting raindrops.

2.2 Lysimeter

Lysimeter consists of a stainless box and a runoff

collector for containing the soil for investigating the soil

erosion in this rainfall simulator experiment. The main

body of lysimeter has inner dimensions of 48 × 33 × 20 cm

(L × W × H). The front side of the stainless box has a height

of 15 cm for installing the runoff collector. The runoff

collector has a triangular shape with an angle of 90 in the

horizontal direction and inclined vertically at 45. The

bottom part of the lysimeter has an outlet to drain the

infiltration water (Fig. 2).

2.3 Experiment for Runoff, Sediment and Infiltration

Outflow

The study of runoff, sediment and infiltration

conducting with the MPPH rainfall simulator used

Andosol soil which brought from the field of Tokyo

University of Agriculture and Technology, Koganei

campus at Latitude of 35.7011108 and Longitude of

139.5180654. The soil was examined for the water content

at the field capacity.

The field soil sample was transferred to a laboratory,

dried in the room temperature for about 7 days and then

sieved by a 2 mm mesh sieve. All the sieved soil was kept

inside plastic bag before the experiment.

2.3.1 Soil Condition and Soil Packing

The designed dry bulk density of the soil was

determined from average value of the field samples. Also,

saturated hydraulic conductivities of the field soil which

was used for the experiments were measured by constant

head method (Dane and Topp, 2002).

The soil packing in 3 lysimeters were performed

following procedure. First, 2 cm of glass beads (diameter

of 1.5 mm to 2.5 mm) layer covered with 500 micron

opening stainless mesh (33 cm wide × 48 cm long) was set

on the bottom of the lysimeter. Next, 1 cm thick soil layer,

then 8 layers of 1.5 cm thick soil layers were packed layer

by layer. During the soil packing, soil layers were

compressed to achieve the designed dry bulk density of

(2)

(3)

Fig. 2 Dimensions of lysimeter box and runoff collector

Ⅰ_299


0.58 × 103 kg m-3 which was measured in the field. Also,

certain amount of water was sprayed by hand sprayer in

order to achieve designed water content which was equal

to the field capacity of 0.39 cm3 cm-3.

The calculation to determine the amount of wet soil (g)

and additional water (cm3) for packing is as follows. First

amount of dry soil (g) required for packing 1 cm high is:

Dry soil =ρb × area (33cm×48cm) × height (4)

where ρb is desired dry bulk density of dry soil (kg m-3).

Next, amount of wet soil stored in the laboratory for

packing 1 cm layer is:

Packing wet soil =Dry soil × θg + Dry soil (5)

where θg is gravimetric water content (kg m-3). Then the

amount of additional water to achieve designed volumetric

water content is:

Water ={θv(Designed)-θv(Lab)} × area × height (6)

where θv(Designed) is designed volumetric water content

(cm3 cm-3) and θv(Lab) is the volumetric water content

(cm3 cm-3) of the soil stored in the laboratory.

The packed soil level was lower than the lysimeter

border 5 cm (Fig. 2). Some splashed of soil during

experiment were trapped with these borders.

2.3.2 Rainfall Intensity Calibration

The calibration of the rainfall intensity was performed

using the plastic calibration tray having the catchment area

of 33 cm × 48 cm placed on the lysimeter which was

covered with the plastic sheet in order to avoid water

entering the packed soil. The 50 years return period was

the frequency that usually used for studying in hydrology

(Jain and Singh, 2003). The designed monsoon rainfall

intensity applied in this study for Japan and the Southeast

Asian countries such as Thailand was 70 mm h-1, (Nhat et

al., 2007; Bureau of Location and Design, Department of

Highway, Thailand, 2010). First, the rainfall intensity of

70 mm h-1 was manually calibrated by collected amount of

water in the plastic tray in 2 minutes. Calculated amount

of rainfall for corresponding intensity and duration was

369.6 g. Calibration criteria was less than 2.6% error for

three consecutive replications.

2.3.3 Runoff and Infiltration Outflow Sampling and

Filtration of Sediment

The runoff and infiltration outflow samples were

collected by using glass bottles placed under the runoff

collector and infiltration outflow outlet of lysimeter,

respectively. The splashed sediment beyond 5 cm border

was considered to be negligible. The time step for

replacing the new bottles was every 10 minutes for 100

minutes after the runoff initiated. The weights of all

samples were measured after sampling. The runoff

samples were filtered to separate the sediment from the

runoff water by using the WhatmanⓇ glass microfiber

filter 60 mm with pore size of 1.6 micrometer. The mass

of sediment in the runoff water samples were recorded.

3. RESULTS AND DISCUSSION

3.1 Calibration of Rainfall Properties

Table 1 shows the number of raindrops and the mass of

raindrops using 0.34 mm needle attached on the PET

bottle. The average number of drops and amount of water

in 2 minutes were 180 drops and 2.21 g, respectively.

Consequently, the average mass of one drop was 0.0123 g.

The raindrop diameter that calculated by using Equation 1

was 2.86 mm.

The rain drop velocity for the MPPH rainfall simulator

obtained graphically from van Boxel (1998) was about 5.2

m s-1. The terminal velocity of the natural raindrop which

had a diameter of 2.86 mm was about 7.8 m s-1 which was

also obtained graphically from the plot presented by van

Boxel (1998). The raindrop velocity of this experiment

was about 67% of the terminal velocity. From Equation 2,

the kinetic energy of rainfall having an intensity of 70 mm

h-1 was calculated to be 0.263 J m-2 s-1 which was close to

Boulange et al. (2019). The kinetic energy at the terminal

velocity was 0.592 J m-2 s-1.

Fig. 3 shows that the results of the calibration of water

pressure head against rainfall intensity. The rainfall

intensity increased linearly as water pressure head

increased. The calibration showed the MPPH rainfall

simulator had ability to produce rainfall intensity from 50

mm h-1 to 110 mm h-1 with R2 of 0.997.

The rainfall distribution was calculated from the cases

of without fan and with fans. The CU values showed that

the uniformities of rainfall distribution were increased

from 64.8% of without fan to 84.3% of with fans. The CU

values of rainfall intensity of 50 mm h-1 and 100 mm h-1

were 81.98% and 84.10%, respectively. In general, CU

values greater than 70% are considered to be acceptable

performance for large plots and CU values greater than

80% are considered to be good performance (Luk et al.,

1993; Martinez-Mena et al., 2001).

3.2 Soil Characteristics and Hydraulic Conductivity

In this experiment, the designed dry bulk density was

determined to be 0.58 × 103 kg m-3, which was an average

No.

Time

(min)

The number of

raindrops

The amount of

water (g)

1

2

3

4

2

2

2

2

184

179

177

181

2.26

2.20

2.15

2.22

Average 2 180 2.21

Table 1 The number of raindrops and the mass of raindrops using

0.34 mm needle

Ⅰ_300


Fig. 3 Calibration results of water pressure head and rainfall intensity

value of measured bulk densities in the field where soils

were collected for the experiment. The average dry bulk

density of field soil in this experiment was slightly greater

than that value studied by Kassaye (2018).

The average value ± standard deviation of measured

saturated hydraulic conductivity was 153 ± 40 cm d-1.

Kassaye (2018) reported that the average saturated

hydraulic conductivity of Andosol soil in Sakaecho field,

Fuchu, Tokyo, Japan was 172 cm d-1.

3.3 Runoff and Infiltration Outflow

Fig. 4 shows the average runoff discharge from Andosol

soil in 100 minutes at slope of 5% and rainfall intensity of

70 mm h-1 in the experiments which was conducted by

using the MPPH rainfall simulator.

The average time ± standard deviation for runoff

initiation was at 98 ± 44.5 seconds after the rainfall

simulation started. The trend of runoff rate increased

rapidly until 20 minutes and gradually became constant

around 52 mm h-1 after 30 minutes. Yadav and Watanabe

(2018) reported that the average runoff discharge until the

end of rainfall simulation on the Andosol soil in the plot

scale experiment in Sakaecho field, Fuchu, Tokyo, Japan

was about 30 mm h-1. The designed dry bulk density of this

experiment was 0.58 which was the same with the

experimental plot reported by Yadav and Watanabe (2018).

Plot scale experiment had the smaller runoff discharge and

greater infiltration as compared with lysimeter experiment

in this study. The soil in the plots was undisturbed and

probably had more macropores therefore infiltration was

greater than disturbed packed soil in the lysimeters.

Presence of macropores in the soil increases the infiltration

and decreases the surface runoff (Smettem, 2009; Mori et

al., 2014).

Fig. 5 shows average infiltration outflow discharged

from the lysimeter. In this experiment, the infiltration

outflow occurred at 60 minutes after the rainfall simulation

was started. After, the average of infiltration rate gradually

increased to 17 mm h-1 (40.8 cm d-1) and became relatively

stable after 70 minutes. The final infiltration rate of 40.8

cm d-1 was appreciably smaller than the hydraulic

conductivity of the field soil (153 cm d-1). This is probably

because of the effects of soil sealing and crusting during

the rainfall simulation. One of the main effects of soil

sealing and crusting is a marked reduction in hydraulic

conductivity and infiltration rate, which triggers runoff and

erosion (Nciizah and Wakindiki, 2015). Final average

runoff discharge was about 52 mm h-1 and corresponding

final average infiltration outflow was about 17 mm h-1. The

total average discharge from the lysimeter was 69 mm h-1

while calibrated rainfall intensity was 70 mm h-1.

Fig. 6 shows the amount of sediment discharge

measured every 10 minutes. The average sediment

concentration in the first 10 minutes was about 3.53 g L-1

and increased rapidly to 5.99 g L-1. Yadav and Watanabe

(2018) reported the average sediment loss of Andosol soil

was about 17 g L-1. The amount of sediment loss depends

on the length of the slope and the longer the slope, the

greater the sediment loss (Kinnell, 2000). The plot

experiment of Yadav and Watanabe (2018) had the slope

length of 5 m while this experiment had 48 cm. In this

experiment, the average value of cumulative sediment

losses was about 3.81 t ha-1 h-1.

Fig. 6 Average sediment discharge from runoff

Fig. 5 Characteristics of infiltration outflow rate

Fig. 4 Average result of runoff discharge

Ⅰ_301


4. CONCLUSION

The study of raindrop characteristics presented that the

raindrop of MPPH rainfall simulator had raindrop velocity

of about 5.2 m s-1 which is about 67% of terminal velocity.

The kinetic energy of rainfall having an intensity of 70 mm

h-1 was calculated to be 0.263 J m-2 s-1, and the kinetic

energy at the terminal velocity was 0.592 J m-2 s-1.

For the rainfall-runoff simulation, the average time for

runoff initiation was at about 98 ± 44.5 seconds after the

rainfall simulation started. The trend of runoff rate

increased rapidly until 20 minutes and gradually became

constant around 52 mm h-1 after 30 minutes. The

infiltration outflow occurred at 60 minutes after the rainfall

simulation was started. The average of infiltration rate

gradually increased to 17 mm h-1 and became relatively

stable after 70 minutes. The average sediment

concentration in the first 10 minutes was about 3.53 g L-1

and increased rapidly to 5.99 g L-1. The average

cumulative sediment loss was about 3.81 t ha-1 h-1.

Finally, the MPPH rainfall simulator demonstrated the

capabilities to use in rainfall-runoff experiments and

produced useful data sets for runoff, infiltration and

sediment discharge.

ACKNOWLEDGMENTS : This study was partly funded by

Japan Science and Technology Agency, SATREPS Grant number

JPMJSA 1505.

Authors are thankful to all the members of the Pesticide Fate

and Transport Laboratory and Environmental Soil Physics and

Engineering Laboratory, Tokyo University of Agriculture and

Technology, for assisting in laboratory experiments.

REFERENCES

Aksoy, H., Unal, N.E., Cokgor, S., Gedikli, A., Yoon, J., Koca, K., Inci,

S.B. and Eris, E. (2012): A rainfall simulator for laboratory-scale

assessment of rainfall-runoff-sediment transport processes over a two-

dimensional flume, CATENA, 98, 63-72.

Boulange, J., Malhat, F., Jaikaew, P., Nanko, K. and Watanabe, H. (2019):

Portable rainfall simulator for plot-scale investigation of rainfall-

runoff, and transport of sediment and pollutants, International Journal

of Sediment Research, 34, 38-47.

Bureau of Location and Design, Department of Highway, Thailand

(2010): Handbook of drainage system design, Part 2.

Dane, J.H. and Topp, G.C. (2002): Methods of Soil Analysis, Part 4

Physical Methods, Soil Science Society of America Book Series, 5,

Soil Science Society of America, 255-293.

Iserloh, T., Fister, W., Seeger, M., Willger, H. and Ries, J.B. (2012): A

small portable rainfall simulator for reproducible experiments on soil

erosion, Soil and Tillage Research, 124, 131-137.

Jain, S.K. and Singh, V.P. (2003): Water Resources Systems Planning and

Management, Developments in Water Science, 51, 555-612.

Kara, T., Ekmekci, E. and Apan, M. (2008): Determining the Uniformity

Coefficient and Water Distribution Characteristics of Some Sprinklers,

Pakistan Journal of Biological Sciences, 11(2), 214-219.

Kassaye, K.T. (2018): Soil moisture monitoring and modeling for

irrigation water management, MS thesis, Graduate School of

Agriculture, Tokyo University of Agriculture and Technology.

Kinnell, P.I.A. (1981): Rainfall intensity-kinetic energy relationships for

soil loss prediction, Soil Science Society of America Journal, 45, 153-

155.

Kinnell, P.I.A. (2000): The Effect of Slope Length on Sediment

Concentrations Associated with Side-Slope Erosion, Soil Science

Society of America Journal, 64(3), 1004-1008.

Kirkby, M.J., Imeson, A.C., Bergkamp, G. and Cammeraat, L.H. (1996):

Scaling up processes and models from the field plot to the watershed

and regional areas, Journal of Soil and Water Conservation, 51(5) 391-

396.

Luk, S.H., Abrahams, A.D. and Parsons, A.J. (1993): Sediment sources

and sediment transport by rill flow and interrill flow on a semi-arid

Piedmont slope, Southern Arizona, CATENA, 20(1-2), 93-111.

Martinez-Mena, M., Castillo, V. and Albaladejo, J. (2001): Hydrological

and erosional response to natural rainfall in a semi-arid

area of south-east Spain, Hydrological Processes, 15, 557-571.

Mori, Y., Fujihara, A. and Yamagishi, K. (2014): Installing artificial

macropores in degraded soils to enhance vertical infiltration and

increase soil carbon content, Progress in Earth and Planetary Science,

1, 30.

Nciizah, A.D. and Wakindiki, I.I.C. (2015): Soil sealing and crusting

effects on infiltration rate: a critical review of shortfalls in prediction

models and solutions, Archives of Agronomy and Soil Science, 61(9),

1211-1230.

Nhat, L.M., Tachikawa, Y., Sayama, T. and Takara, K. (2007): Regional

rainfall intensity-duration-frequency relationships for ungauged

catchments based on scaling properties, Annuals of Disaster

Prevention Research Institute, Kyoto University, 50(B), 33-43.

Oldeman, L.R., Hakkeling, R.T.A. and Sombroek, W.G. (1991): World

map of the status of human-induced soil degradation, Global

Assessment of Soil Degradation (GLASOD), International Soil

Reference and Information Centre, p.21.

Pimentel, D., Harvey, C., Resosudarmo, P., Sinclair, K., Kurz, D.,

McNair, M., Crist, S., Shpritz, L., Fitton, L., Saffouri, R. and Blair, R.

(1995): Environmental and economic costs of soil erosion and

conservation benefits, Science, 267(5201), 1117-1123.

Smettem, K.R.J. (2009): The relation between runoff generation and

temporal stability of soil macropores in a fine sandy loam, Biologia,

64(3), 470-473.

van Boxel, J. (1998): Numerical model for the fall speed of raindrops in

a rainfall simulator, I.C.E. Special Report, 1, 77-85.

Wudneh, A., Erkossa, T. and Devi, P. (2014): Sediment and nutrient lost

by runoff from two watersheds, Digga district in Blue Nile basin,

Ethiopia, African Journal of Environmental Science and Technology,

8(9), 498-510.

Yadav, I.C. and Watanabe, H. (2018): Soil erosion and transport of

Imidacloprid and Clothianidin in the upland field under simulated

rainfall condition, Science of the Total Environment, 640–641, 1354-

1364.

Ⅰ_302


〔Received 2019. 3. 15，Accepted 2019. 8. 30〕

development of mini portable pressure head type rainfall

Documents