Practice for Measurement of the Kinetic Energy of Simulated Rainfall

2020 ◽  
Author(s):  
2021 ◽  
Author(s):  
Harris Ramli ◽  
Siti Aimi Nadia Mohd Yusoff ◽  
Mastura Azmi ◽  
Nuridah Sabtu ◽  
Muhd Azril Hezmi

Abstract. It is difficult to define the hydrologic and hydraulic characteristics of rain for research purposes, especially when trying to replicate natural rainfall using artificial rain on a small laboratory scale model. The aim of this paper was to use a drip-type rainfall simulator to design, build, calibrate, and run a simulated rainfall. Rainfall intensities of 40, 60 and 80 mm/h were used to represent heavy rainfall events of 1-hour duration. Flour pellet methods were used to obtain the drop size distribution of the simulated rainfall. The results show that the average drop size for all investigated rainfall intensities ranges from 3.0–3.4 mm. The median value of the drop size distribution or known as D50 of simulated rainfall for 40, 60 and 80 mm/h are 3.4, 3.6, and 3.7 mm, respectively. Due to the comparatively low drop height (1.5 m), the terminal velocities monitored were between 63–75 % (8.45–8.65 m/s), which is lower than the value for natural rainfall with more than 90 % for terminal velocities. This condition also reduces rainfall kinetic energy of 25.88–28.51 J/m2mm compared to natural rainfall. This phenomenon is relatively common in portable rainfall simulators, representing the best exchange between all relevant rainfall parameters obtained with the given simulator set-up. Since the rainfall can be controlled, the erratic and unpredictable changeability of natural rainfall is eliminated. Emanating from the findings, drip-types rainfall simulator produces rainfall characteristics almost similar to natural rainfall-like characteristic is the main target.


2020 ◽  
Author(s):  
Nives Zambon ◽  
Lisbeth Lolk Johannsen ◽  
Peter Strauss ◽  
Tomáš Dostál ◽  
David Zumr ◽  
...  

<p>Soil erosion by water is globally the main soil degradation process which leaves serious consequences on agricultural land and water aquifers. Splash erosion is the initial stage of soil erosion by water, resulting from the destructive force of rain drops acting on soil surface aggregates. Splash erosion studies conducted in laboratories use rainfall simulators. They produce artificial rainfall which can vary according to type of the rainfall simulator. In this study the aim was to quantify the differences in splash erosion rates affected by rainfall produced by two different rainfall simulators on two silt loam and one loamy sand soil. Splash erosion was measured using modified Morgan splash cups and the rainfall simulators were equipped with four VeeJet or one FullJet nozzle. The soil samples placed under simulated rainfall were exposed to intensity range from 28 to 54 mm h<sup>-1</sup> and from 35 to 81 mm h<sup>-1</sup>, depending on the rainfall simulator. Rainfall characteristics such as drop size and velocity distribution were measured with an optical laser disdrometer Weather Sensor OTT Parsivel Version 1 (Parsivel) by OTT Messtechnik. Rainfall simulator with VeeJet nozzles produced smaller drops but higher drop velocity which resulted in higher kinetic energy per mm of rainfall compared to rainfall simulator with FullJet nozzles. For the same intensity rate measured kinetic energy under the rainfall simulator with VeeJet nozzles was 45% higher than rainfall kinetic energy from rainfall simulator with FullJet nozzles. Accordingly, the average splash erosion rate was 45 and 59% higher under the rainfall simulator with VeeJet nozzles for one silt loam and loamy sand soil, respectively. Splash erosion was found to be a linear or power function of the rainfall kinetic energy, depending on rainfall simulator. The obtained results highlight the sensitivity of the splash erosion process to rainfall characteristics produced by different rainfall simulators. The heterogeneity of rainfall characteristics between different types of rainfall simulators makes a direct comparison of results obtained from similar erosion studies difficult. Further experiments including comparison between more rainfall simulators could define influencing rainfall parameters on splash erosion under controlled laboratory conditions.</p>


2016 ◽  
Vol 61 (13) ◽  
pp. 2435-2442 ◽  
Author(s):  
Yoshinori Shinohara ◽  
Sohei Otani ◽  
Tetsuya Kubota ◽  
Kyoichi Otsuki ◽  
Kazuki Nanko

CATENA ◽  
2016 ◽  
Vol 137 ◽  
pp. 237-243 ◽  
Author(s):  
Derege Tsegaye Meshesha ◽  
Atsushi Tsunekawa ◽  
Mitsuru Tsubo ◽  
Nigussie Haregeweyn ◽  
Firew Tegegne

ael ◽  
2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Kenneth M. Wacha ◽  
Chi‐hua Huang ◽  
Peter L. O'Brien ◽  
Athanasios N. Papanicolaou ◽  
Jerry L. Hatfield

2018 ◽  
Vol 13 (No. 4) ◽  
pp. 226-233 ◽  
Author(s):  
Petrů Jan ◽  
Kalibová Jana

Rainfall characteristics such as total amount and rainfall intensity (I) are important inputs in calculating the kinetic energy (KE) of rainfall. Although KE is a crucial indicator of the raindrop potential to disrupt soil aggregates, it is not a routinely measured meteorological parameter. Therefore, KE is derived from easily accessible variables, such as I, in empirical laws. The present study examines whether the equations which had been derived to calculate KE of natural rainfall are suitable for the calculation of KE of simulated rainfall. During the experiment presented in this paper, the measurement of rainfall characteristics was carried out under laboratory conditions using a rainfall simulator. In total, 90 measurements were performed and evaluated to describe the rainfall intensity, drop size distribution and velocity of rain drops using the Thies laser disdrometer. The duration of each measurement of rainfall event was 5 minutes. Drop size and fall velocity were used to calculate KE and to derive a new equation of time-specific kinetic energy (KE<sub>time</sub> – I). When comparing the newly derived equation for KE of simulated rainfall with the six most commonly used equations for KE<sub>time</sub> – I of natural rainfall, KE of simulated rainfall was discovered to be underestimated. The higher the rainfall intensity, the higher the rate of underestimation. KE of natural rainfall derived from theoretical equations exceeded KE of simulated rainfall by 53–83% for I = 30 mm/h and by 119–275% for I = 60 mm/h. The underestimation of KE of simulated rainfall is probably caused by smaller drops formed by the rainfall simulator at higher intensities (94% of all drops were smaller than 1 mm), which is not typical of natural rainfall.


Author(s):  
Petrů Jan ◽  
Kalibová Jana

Rainfall characteristics such as total amount and rainfall intensity (I) are important inputs in calculating the kinetic energy (KE) of rainfall. Although KE is a crucial indicator of the raindrop potential to disrupt soil aggregates, it is not a routinely measured meteorological parameter. Therefore, KE is derived from easily accessible variables, such as I, in empirical laws. The present study examines whether the equations which had been derived to calculate KE of natural rainfall are suitable for the calculation of KE of simulated rainfall. During the experiment presented in this paper, the measurement of rainfall characteristics was carried out under laboratory conditions using a rainfall simulator. In total, 90 measurements were performed and evaluated to describe the rainfall intensity, drop size distribution and velocity of rain drops using the Thies laser disdrometer. The duration of each measurement of rainfall event was 5 minutes. Drop size and fall velocity were used to calculate KE and to derive a new equation of time-specific kinetic energy (KE<sub>time</sub> – I). When comparing the newly derived equation for KE of simulated rainfall with the six most commonly used equations for KE<sub>time</sub> – I of natural rainfall, KE of simulated rainfall was discovered to be underestimated. The higher the rainfall intensity, the higher the rate of underestimation. KE of natural rainfall derived from theoretical equations exceeded KE of simulated rainfall by 53–83% for I = 30 mm/h and by 119–275% for I = 60 mm/h. The underestimation of KE of simulated rainfall is probably caused by smaller drops formed by the rainfall simulator at higher intensities (94% of all drops were smaller than 1 mm), which is not typical of natural rainfall.  


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