development of mini portable pressure head type rainfall
TRANSCRIPT
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).
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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
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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
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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
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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
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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.
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〔Received 2019. 3. 15,Accepted 2019. 8. 30〕