IJERD – International Journal of Environmental and Rural Development (2017) 8-1

Research articleerd

Development of Portable Artificial Rainfall Simulator forEvaluating Sustainable Farming in Kenya
JACOB MURIUNGI MAORE
Graduate School of Agriculture, Tokyo University of Agriculture, Tokyo, Japan
Email: maorej@yahoo.com

MACHITO MIHARA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: m-mihara@nodai.ac.jp
Received 30 December 2016

Accepted 5 May 2017(*Corresponding Author)

Abstract Artificial rainfall simulation is an important aspect to investigate soil erosion process
and surface runoff through application of rainfall simulator. On the other hand portable artificial
rainfall simulator can be utilized in remote areas to solve some of the challenges that may beposed by heavy and expensive factory-made rainfall simulators at the same time maintaining
the effectiveness and efficiency of the equipment. Drop size, kinetic energy, surface runoff andsediment yield were obtained from experiments conducted using artificial portable rainfall
simulator developed in the lab of land and water use engineering for testing on actual fields
with different vegetation cover in Kenya. Average kinetic energy and drop size calculated from24 outlet needles of the rainfall simulator was found to be approximately 1.6 x 10-5 J and 3.42mm respectively. Using calibrated cylinder, intensity was measured randomly along thesimulator needle outlets and average intensity calculated as 40 mm hr-1. Water pressure wasgenerated through elevated Marriote bottle. Experiments were conducted in research site inMombasa Kenya. Drop size and kinetic energy for actual rainfall in Kenya were also
determined. Evaluation of soil erosion using portable artificial rainfall simulator is therefore
important in establishment of proper and effective soil erosion control strategy for achieving
sustainable farming in Kenya.
Keywords rainfall simulator, soil erosion, sustainable farming, portable, Mombasa Kenya

INTRODUCTION
Kenya is located in Eastern part of Africa and It lies between latitudes 5°N and 5°S, and longitudes 34°
and 42°E and its total area is 582,650 km2. It borders five countries (Tanzania, Uganda, Sudan,Ethiopia and Somali) and Indian Ocean on south eastern part. Agriculture in Kenya faces various
challenges like water shortage, soil erosion, inadequate technical farming knowledge etc.
Research on soil erosion through application of portable rainfall simulator is among the basic
steps necessary in improving sustainable agriculture. Although water is considered as the most criticalresource for sustainable agricultural development worldwide (Konstantinos et al., 2015), soil erosion
control is also one of the factors considered in enhancing sustainable agriculture. Rainfall
aggressiveness has always been a prominent environmental threat in the course of human history,especially affecting the agricultural sector (Nazzareno et al., 2010). Rainfall intensity, drop size, drop
fall velocity and kinetic energy are considered in determination of rainfall effect on the soil whereas
together with other factors like vegetation cover, land slope, soil erodibility and support practice can beapplied to estimate amount of soil loss.
Rainfall simulators have been developed and used extensively for runoff, infiltration and erosion
data collection for several years (Roberto et al., 2013). Approximately, for the last 75 years rainfallⒸ ISERD27IJERD – International Journal of Environmental and Rural Development (2017) 8-1

simulators have been developed and used throughout to conduct research on infiltration, surface waterrunoff and soil erosion (Humphry et al., 2002). Weight, efficiency, cost and portability are among themajor factors considered in development of rainfall simulators. They have produced raindrops either
through nozzles or tubing tips like hollow needles. In this research, more emphasis is put on simulatorsthat utilize hollow needles and require lower pressure as compared to those that use nozzles.
Development of portable rainfall simulator can be achieved through utilization of readily available
materials and a Marriott bottle for evenly distributed water pressure generation.
Many of the existing rainfall simulators are laboratory tools suited for working with disturbed soil
samples in shallow trays (Abudi, 2011). Data from the actual fields can yield better analytical results ascompared to prepared laboratory plots and provides more actual conditions for further research. Simple
design of portable rainfall simulator facilitates extensive research to be done in many fields. In thisstudy more emphasis is put on how to develop portable artificial rainfall simulator and evaluate soil
erosion through application of portable artificial rainfall in different fields and appropriate soil erosion
control measures to improve environmental factors and also promote economic factors leading toincreased farm output.
OBJECTIVE
To develop portable artificial rainfall simulator with Marriott bottle and to evaluate soil erosion on
agriculture field through observing soil loss in different fields condition under a portable artificial
rainfall simulator for sustainable farming practices in Kenya.
METHODOLOGY
Rainfall simulators are commonly used instruments to study sheet erosion, since they can be set topredefined values such as rainfall duration and quantity (Schindler et al., 2012). Development ofaffordable portable artificial rainfall simulator can therefore be utilized in solving some of thechallenges that may be posed by heavy and expensive factory made rainfall simulators at the same time
maintaining the effectiveness and efficiency of the equipment.
Materials: Locally available materials were used to develop portable artificial rainfall simulator which
includes; 2 pieces of PVC pipes 1 meter long each and 8 mm internal diameter, outlet needles 0.83 mm
internal diameter, connecting plastic pipes with control valves, Marriott bottle and metallic stand.
Twelve holes were drilled 8 cm apart on each pipe and outlet needles 0.83 mm internal diameter
fixed tightly to allow evenly distributed water drops. Marriott bottle was attached for constant pressure
head as shown in Fig. 1.

ABCDFig. 1 Materials for artificial potable rainfall simulator Fig. 2 Needles numbering and groupingUsing simple metallic stands, developed rainfall simulator was suspended horizontally and firmly
at a height of 73 cm from the base and Marriott bottle connected approximately 83 cm from the base toⒸ ISERD28

IJERD – International Journal of Environmental and Rural Development (2017) 8-1

generate equal and evenly distributed pressure and maintain a constant head of water. The experiments
were conducted in laboratory to determine intensity, drop size, drop velocity and kinetic energy of theraindrop simulated. Filter paper method was used to determine drop size, whereas camera method wasused to determine drop velocity. Kinetic energy is calculated by mathematical relationship of drop
mass and velocity. Drops from all 24 needles were collected and considered individually. Also, theintensity of the raindrops from simulator developed were also measured since it is crucial in therelationship between rainfall intensity and kinetic energy and its variations in time and space isimportant for erosion prediction (Van Dijk, 2002).
Raindrop size measurement: Using a filter paper, drops were collected individually and approximate
diameter of each circle formed by the rain drop measured and the average diameter calculated using
equation 1. To determine mass of the rain drop, its volume was calculated and multiplied with waterdensity.
d = 0.141d’+0.888 (m)

(1)

3

3

𝑉𝑜𝑙 = π/6𝑑 (m )(2)

𝑀 = 𝑉𝑜𝑙∗𝐷 = 𝑉𝑜𝑙∗1000 (𝑘𝑔)(3)

Where d is assumed diameter of spherical drop (m), d’ Diameter of the drop on the filter paper(m), M Mass of the drop (kg), and D Density of water (1000 kg/m3).
Raindrop velocity: Rain drop velocity was calculated using the camera method and applying equation
4. Distance travelled refers to height covered by a falling raindrop represented by image captured bycamera at a known camera shutter speed.
ms

Velocity ( ) =Distance (m)Time( s)(4)Time represents the camera shutter speed which is set as 1/100 seconds of camera shutter anddistance in meters represents the height captured by camera shutter covered by the falling drop.
Raindrop kinetic energy: Raindrop kinetic energy was determined from product of mass and raindrop
velocity.
𝐾𝐸𝐷 =1
𝑀𝐷 𝑉𝐷 22(5)Where KED is kinetic energy (J), MD raindrop mass (kg), and VD Drop velocity (m/s).
Pressure generated by Marriott bottle: For production of desired intensity over a period of time, it isimportant to supply equal water pressure which can be achieved by maintaining constant water head
Pressure = h x ᵨ x g (Pa)(6)
3Where h is head difference (m), ᵨ density of liquid (kg/m ), and g gravitational force (m/s2).
Actual rain drop observation in Kenya: Drop size determination by filter paper method and drop
velocity determination by camera method were also applied in actual rainfall in Kenya for comparison
with simulated drop characteristics. Several other methods which are more complicated and expensive
but more precise are applied to determine the size of the raindrop and drop velocity. The simple filter
paper and camera methods were applied for easy and quick comparison with simulated raindrop.
Evaluation of soil erosion through application of developed simulator in the field: Runoff plots
were designed by isolating an area in the field of 1.1 m long by 0.2 m wide and sheet metal inserted
around to a depth of approximately 0.2 m below the ground. After leaving the place wet overnight,
surface runoff was collected at an interval of five minutes. Six samples from each of the four different
field conditions were collected and each sample was measured and recorded. Soil lose was also
determined by oven drying surface runoff collected.

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IJERD – International Journal of Environmental and Rural Development (2017) 8-1

RESULTS AND DISCUSSION
Raindrop Diameter and Kinetic Energy
Size of raindrop is defined by its diameter assuming that the raindrop is spherical. Size and kinetic
energy of each of the twenty four needles was calculated and graphically represented as shown in Fig.
3. Average kinetic energy was calculated as 1.6 x10-5 J and raindrop size approximately 3.42 mm.
Actual raindrops have different sizes but in average according to many researchers, they ranges
between 0.5 mm to 5 mm. Simulated raindrop is therefore within this range.
4.0
3.0

2.0

2.0
1.0

1.0

0.0

0.0
7 9 11 13 15 17 19 21 23
Simulator needle number
Kinetic energy (x10-5) J
Raindrop diameter (mm)13Raindrop diameter(mm)

Kinetic energy(x10-5) J

3.05

2.00

a*a*a*a*4.00

Mean drop diameter(mm)

Mean kinetic energy(x10-5) JFig. 3 Kinetic Energy and raindrop diametera*a*

a*a*ABC
Needle groups

D3.00
2.00

1.00

1.00

0.00
AB
C
Needle groups

0.00

D

**p< 0.01, *p< 0.05**p< 0.01, *p< 0.05

Fig. 4 Mean kinetic energy and mean drop diameter statistical analysis
As shown in Fig. 4, according to needle grouping A, B, C and D, there was no statisticaldifference among the means for both drop size and kinetic energy. This indicates that pressure
calculated as 981 Pa was uniformly distributed among all the needles and the drops impact on theground is fairly uniform. Also using a measuring container, intensity was measured directly from four
sections of the rainfall simulator and average intensity was calculated as 40 mm/hour. Actual rainfall
intensity has a wide range depending on the amount of rain per specific time. Raindrop from thisdeveloped simulator utilizes gravity and its own weight to fall. Similarly homogeneous pressure
generated through Marriott bottle is due to gravity.

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IJERD – International Journal of Environmental and Rural Development (2017) 8-1

Actual Rainfall Drop in Kenya and Simulated Drop Characteristics

Simulator drop occurrences

Simulator drop occurrences
Natural rain drop occurrences

30

Cumulative(Occurrencies)

Cummulative(Occurrences)

Actual raindrops differ with the simulated drops since it’s hard to maintain same drop velocity, shapeand size throughout the experiment as compared to simulated ones. Therefore, application of camera
method and filter paper to determine drop velocity and drop size respectively for actual rainfall wasapplied purposely to obtain an estimate of these characteristics range and for comparison purposes.
After sampling 22 actual raindrops and determining their drop velocity, average velocity wascalculated as 1.38 m/s compared to average simulated raindrop velocity of 1.23 m/s. To determine
actual rainfall drop size, 58 raindrops were sampled and average drop size calculated as 3.94 mm
which is slightly higher than average of simulated raindrop which was calculated as 3.42 mm.

20100

Natural rain drop occurrences

6050403020100

Drop size range (mm )Drop velocity range (m/s )Fig. 5 Natural rain drop and simulator drop relation on drop velocity and drop size
From Fig. 5, drop size, drop velocity and kinetic energy were found to be within the range
although actual rain drop size varied greatly. Portable artificial rainfall simulator can therefore beapplied in the field to simulate rainfall which is comparable to actual rain for evaluation of soil erosion.
Maize field
Grass land
Uncultivated land
Cowpeas field

3000

100Soil loss (mg l-1)
(x 10 3')

Runoff discharge(mm min-1)

4000

2000

10000Maize field
Grass land
Uncultivated land
Cowpeas field80
6040
20005101520Time (mins)

2530

05101520Time (mins)

2530Fig. 6 Runoff discharge and soil loss graphs for different soil field types
Evaluation of Soil Erosion through Application of Developed Simulator in the Field
Surface runoff was collected at an interval of 5 minutes on 1.2 m by 0.2 m plot on undisturbed soil.
According to Fig. 6, developed portable rainfall simulator was applied to evaluate soil erosion in four
different fields. Quantitative surface runoff and soil loss was calculated. Highest soil loss and highestⒸ ISERD31

IJERD – International Journal of Environmental and Rural Development (2017) 8-1

surface runoff was observed at maize field since the soil was looser due to frequent cultivation ascompared to uncultivated field and probably due to less vegetation cover as compared to other fields.
This indicates that better soil conservation measures are necessary to reduce soil erosion for sustainable
farming practices in Kenya, depending on soil erosion rate, type of soil, water availability, different
fields’ vegetation cover and amount of rainfall among other related factors.
CONCLUSION
Portability of the rainfall simulator allows the researcher to work in remote areas in Mombasa Countyand Simple installation can be an added advantage in performing timely, effective and efficientresearch. Development of affordable and simple but effective artificial rainfall simulator encourages
more research on soil erosion to be conducted in different fields which would otherwise been difficult
especially in developing countries.
Calibration through experiment indicated that portable artificial rainfall simulator connected toMarriott bottle for pressure generation produces simulated rain drop of approximately 3.42 mm andkinetic energy of approximately 1.6 x10-5 J for soil erosion impact study. Through statistical analysis
the simulated drops had no statistical difference both for the drop size and drop kinetic energy.
Moreover, characteristics of the simulated drops were within the range of the actual rain drops inKenya. This implies that the developed rainfall simulator can be effectively applied in field
experiments.
Evaluation of soil erosion using portable artificial rainfall simulator is important since soil erosion
is among the leading challenges faced by farmers. Soil with less cover and more cultivated are easily
eroded, therefore proper and effective soil erosion control strategy establishment is important forachieving sustainable farming in Kenya. Since terraces are common practice of soil erosion control but
less effective, better strategies like thick vegetation cover and trees are recommended to reduce directcontact of raindrops with the soil.
ACKNOWLEDGEMENTS
The authors acknowledge the support of members of Lab. of Land and Water Use Engineering and thefinancial support from Japan International Cooperation Agency and Tokyo University of Agriculture.
REFERENCES
Abudi, G. and Berliner, P. 2011. Rainfall simulators for field runoff studies, Journal of Hydrology, 76-8, 454-455.
Humphry, J., Daniel T., Edwards D. and Sharpley A. 2002. A Portable rainfall simulator for plot-scale runoff
studies, 18 (2), 199-204.
Konstantinos, C. and Maria, B. 2015. Sustainable water management in agriculture under climate change.
Proceedings of Agriculture and Agricultural Science, 4, 88-98.
Nazzareno, D. and Gianni, B. 2010. A rainfall erosivity model for the Mediterranean region. Journal ofHydrology 387, 119-127.
Roberto, C., Tiffany, W. and Leo, P. 2013. On the estimation of surface runoff through a new plot scale rainfall
simulator in Sardinia, Italy. Proceedings of Environmental Sciences, 19, 875-884.
Schindler, Y., Wildhabera, D., Bänningera, K. and Burrib, C. 2012. Evaluation and application of a portable
rainfall simulator on subalpine grassland. CATENA, 91, 56-62.
Van, D., Bruijnzeel, L. and Rosewell, C. 2002. Rainfall intensity-kinetic energy relationships. Journal ofHydrology, 261, 1-23.

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