Research Article  Open Access
Universal Power Law for Relationship between Rainfall Kinetic Energy and Rainfall Intensity
Abstract
Rainfall kinetic energy has been linked to linear, exponential, logarithmic, and powerlaw functions using rainfall intensity as an independent variable. The power law is the most suitable mathematical expression used to relate rainfall kinetic energy and rainfall intensity. In evaluating the rainfall kinetic energy, the empirical power laws have shown a larger deviation than other functions. In this study, universal power law between rainfall kinetic energy and rainfall intensity was proposed based on the rainfall power theory under an ideal assumption that dropsize is uniformly distributed in constant rainfall intensity. An exponent of the proposed power law was 11/9 and coefficient was estimated at 10.3 from the empirical equations of the existing powerlaw relation. The rainfall kinetic energy calculated by universal power law showed >95% concordance rate in comparison to the average values calculated from exponential and logarithmic functions used in soil erosion model such as USLE, RUSLE, EUROSEM, and SEMMA and <5% relative difference as compared to the average rainfall kinetic energies calculated by other empirical functions. Therefore, it is expected that power law of ideal assumption may be utilized as a universal power law in evaluating rainfall kinetic energy.
1. Introduction
Soil erosion is a natural process in all landform evolution and soil degradation along with various environmental problems. In water erosion, the impact of raindrop on the soil surface disperses soil aggregates. The rainfall kinetic energy is one of the useful indicators in the potential ability of rainfall for separating soil particles from the soil surface. Basically, the rainfall kinetic energy results from the kinetic energy of individual raindrops that strikes the soil. The calculation of the rainfall kinetic energy requires dropsize, dropvelocity, and dropvolume measurements as well as dropsize distribution (DSD). DSD data has been obtained using various techniques such as filter paper, flour pellet, camera, optical array, and meteorological radar [1–7]. The rainfall kinetic energy can be calculated by the measured DSD combined with empirical laws [8–10], direct measurement using a pressure transducer or acoustic devices [11, 12] or using an Optical Spector Pluviometer allowing the real time measurement of dropsize and dropvelocity [7]. Many empirical equations of the rainfall kinetic energy () linked to the easily available rainfall intensity are proposed on the basis of dropsize and dropvelocity measurements. The empirical equations for the rainfall kinetic energy in various mathematical expressions have been developed in the form of powerlaw, exponential, logarithmic, and linear functions.
In the empirical soil erosion models, the rainfall kinetic energy has been used as erosivity factor of splash erosion, sheet erosion, and rill erosion modeling [13–16]. USLE [13], soil erosion models based on agricultural area in the United States, used a logarithmic function of rainfall kinetic energy developed by Wischmeier and Smith [13], and RUSLE [14] used an exponential function proposed by Brown and Foster [17]. Under the assumption based on the DSD measurements [18], EUROSEM [15], the representative soil erosion model in Europe, used a logarithmic function presented by Brandt [19]. SEMMA [16] developed in South Korea adopted an exponential function of Van Dijk et al. [20]. However, they require the validation in a wide range of environmental settings since these functions were focused on restricted areas with different environmental settings and measurement technique.
There are no distinct criteria on what is the most suitable function as rainfall erosivity factor of the soil erosion. Many researchers suggested that the maximum value of the rainfall kinetic energy exists in the natural rainfall events [3, 17, 21–24]. The exponential function which converges to the limited value was judged to be function that better describes the relationship between rainfall kinetic energy and rainfall intensity [3, 25] because there is no upper limit in the powerlaw, logarithmic, and linear functions. Van Dijk et al. [20] proposed a general equation of the exponential type from the measured data through a literature review on the relationship between rainfall kinetic energy and rainfall intensity. The empirical powerlaw relation from the observation of rainfall intensity and radar reflectivity factors using a statistical model of the DSD was presented by Smith and de Veaux [26]. In particular, Salles et al. [27] proved that the timespecific kinetic energy is the most appropriate expression of the empirical law between rainfall kinetic energy and rainfall intensity in the statistical and physical basis and presented that the power law between rainfall kinetic energy and rainfall intensity is the most suitable mathematical function as considering the DSD models.
The existing empirical equations between rainfall kinetic energy and rainfall intensity showed significantly different coefficients according to geographical location and measurement technique. Therefore, it is not easy to apply in other countries or regions having different types of rainfall [4, 20, 28]. In particular, power law in calculation of rainfall kinetic energy shows larger deviation compared to exponential and logarithmic functions [26, 29]. There were few cases that the power law had been used as rainfall erosivity index in developed soil erosion models although it is simple and suitable mathematical expression. Therefore, it is necessary to present the representative power law obtained from various rainfall kinetic energy equations. This study attempts to propose a new equation of power law based on the rainfall power theory under the ideal assumption that dropsize is uniformly distributed in constant rainfall intensity. In addition, our newly proposed power law is evaluated through comparing with existing empirical equations.
2. Theory
2.1. Relationship between Rainfall Kinetic Energy and Rainfall Intensity
In general, the relationships between rainfall kinetic energy and rainfall intensity are presented in the form of exponential [4, 17, 24, 28, 30–34], logarithmic [3, 13, 28, 34–37], linear [24, 28, 38–40], and powerlaw [26, 28, 29, 33, 41, 42] functions.
The rainfall kinetic energy can be expressed in two ways of volumespecific and timespecific kinetic energy. The volumespecific kinetic energy is expressed as the amount of rainfall kinetic energy expended per unit volume of rain [13, 20, 36, 43] while timespecific kinetic energy is the rate of expenditure of rainfall kinetic energy or rainfall power and expressed as rainfall kinetic energy expended per unit area and per unit time [3, 26, 29]. In the relationship between rainfall kinetic energy and rainfall intensity, the two expressions of volumespecific rainfall kinetic energy (J/m^{2}/mm) and timespecific rainfall kinetic energy (J/m^{2}/h) are related to each other through the rainfall intensity as shown in the following:
As reported by SempereTorres et al. [39], the scatterplots of have less heteroscedasticity than those of , and is more sensitive to the DSD of rainfall [27] so that the connection of with is more suitable compared to . Therefore, this study investigates the relationship between timespecific rainfall kinetic energy (hereafter, ) and rainfall intensity.
Exponential, logarithmic, linear, and powerlaw functions of timespecific rainfall kinetic energy can be expressed as general equations using empirical coefficients of , , and as shown in the following equations:
Reported empirical relationships between rainfall kinetic energy and rainfall intensity are summarized in Table 1. In case of exponential function developed widely, only reliable functions organized by Salles et al. [27] and Van Dijk et al. [20] were reported as considering the range of rainfall intensity and the number of observations and determination coefficient of measured data. Also, the linear and logarithmic function include the reliable empirical equations along with equations organized by Salles et al. [27]. Representative forms of the power law include six typical power laws presented using DSD data from the Illinois State Water Survey of the Unites States [26] and six different sets on power law between rainfall related variables and rainfall intensity were presented based on different assumptions regarding the rainfall intensity dependence of the DSD parameters [29]. With continuous and direct dropsize and dropvelocity measurements, kinetic energy equations recently developed in the Republic of Korea were organized in Table 1 [33, 34, 42].

2.2. Review of Mathematical Power Laws
Many researchers demonstrated that a power law is the most suitable mathematical function between rainfall kinetic energy and rainfall intensity [27, 44]. Therefore, the power law presented by Salles et al. [27] is summarized in these passages to understand a mathematically rational power law used to link with.
The timespecific rainfall kinetic energy (J/m^{2}/h), the rainfall kinetic energy flux density [41, 45], is calculated by the DSD and dropvelocity measurement data:where is the water density (kg/m^{3}) in standard conditions, is a diameter of raindrop (cm), is the number of drops with diameter arriving per unit time and per unit area, and is the terminal fall velocity of a raindrop with diameter .
Rainfall intensity (mm/h) is derived from the droplet flux density:
SempereTorres et al. [44, 46] mentioned the various mathematical expressions of the DSD described by exponential, gamma, lognormal, or Weibull distribution functions [18, 47–49] and presented that all DSD models follow the power law as the most appropriate relationship between and . The general formulation of the DSD using as reference variable is expressed as follows:The general formulation of an analytical relation between and is expressed by raindrop flux density replacing DSD and the terminal fall velocity:Using a terminal fall velocity and the variable (9) becomesThe remaining terms except are defined as being a constant. If proposed by Atlas and Ulbrich [50] is used, and can be expressed simply as follows:
The exponent of the relation between and depends on only one variable . In various climate conditions, the coefficient is well expressed by gamma distribution with a single free variable presented by SempereTorres et al. [46] or Salles et al. [51]. Therefore, the coefficient is simply expressed below:
Finally, the power law of (J/m^{2}/h) presented by Salles et al. [27] is described as follows:
In the presented relationship, the parameters and are linked to the type of microphysical process related to the growth of raindrops [27]. In the previously reported studies, is applicable to the range between 30 and 40. Typical values around 30 are related to convective rainfall [44, 46, 51] and the values and are commonly associated with stratified rainfall [18] and drizzle [52], respectively. Regarding the parameter , Marshall and Palmer [18] reported values around 0.12 to 0.15 are suitable to convection rainfall and the value is related to a wide range of stratified rainfall. In the general form of given power law in (5), the coefficient and exponent are transformed into mathematical power functions of Salles et al. [27] as shown below:
The coefficient of the power law is 13.5 for convective rainfall and 9.2 for the wide range of stratified rainfall. The exponent varies from 1.0 to 1.4, and the values around 1 are suitable for strong rainfall.
3. Establishment of Ideal Equation for Rainfall Power
Despite the definition of the functional relationship between rainfall kinetic energy and rainfall intensity, exponents and coefficients of the power law are largely different depending on parameters such as rainfall type, geographical location, and measurement techniques. Therefore, a general equation which represents empirical power law is required to evaluate soil erosion in the area where there is no measurement data of rainfall kinetic energy. The power of raindrop falling on the surface soil is derived theoretically under the ideal assumption that the diameter of raindrop is uniform for constant rainfall intensity. This assumption is based on the judgment that the error caused by this ideal assumption would be smaller than the difference in rainfall kinetic energies estimated by various types of empirical power law [26, 29].
The power of raindrop particles striking on the surface soil is defined by the multiplication of the force and terminal velocity of freefalling raindrop:where rainfall power is the expended energy per unit area and per time (J/m^{2}/s), the force of rainfall is the water weight per unit area (N/m^{2}), and is the terminal velocity of raindrop (m/s).
Atlas and Ulbrich [50] have suggested the power law based on the terminal velocity data presented by Gunn and Kinzer [9]; the terminal fall velocity is proportional to the diameter of raindrop:where is mean diameter (cm) of uniform raindrop.
A freefalling raindrop is affected by gravity and the resistance force. The velocity of a falling raindrop keeps the steady condition when two forces are equal. The terminal fall velocity can be expressed as reported by Zhou et al. [53]:where is the acceleration by gravity (m/s^{2}) and is the constant in the certain range of raindrop diameter (kg s/m^{3}). Therefore, the relationship of the terminal velocity and raindrop diameter is expressed as .
If the raindrop flux density is the number of raindrops with a uniform diameter per unit area and per unit time, rainfall intensity equation can be expressed simply as follows:
The above equation is expressed into the equation of uniform diameter of raindrop as follows:
The uniform diameter in (19) is substituted in the terminal velocity of (16) and it is then substituted in rainfall power equation as follows:
Since the weight of rainfall per unit area is the product of the specific weight and rainfall amount, it is derived fromwhere is the unit weight of raindrop water (N/m^{3}) and the amount of rainfall (mm) has relationship of with rainfall intensity.
When the weight of rainfall in (21) is substituted in the rainfall power equation, it is expressed as in the following:
If the equation of rainfall power per unit area (J/m^{2}/s) is converted to the equation of timespecific rainfall kinetic energy (J/m^{2}/h), and time is 1 hour, the ideal equation of rainfall power is derived as follows:
Therefore, timespecific rainfall kinetic energy () from rainfall power theory is proportional to 11/9 power of rainfall intensity and is in inverse proportion to 2/9 power of the number of raindrops, .
The exponent 11/9 of rainfall power function was theoretically derived from ideal assumption that the dropsize is uniform in constant . The coefficient can be calculated if the number of raindrops is identified. DSD to describe a population of falling drops obviously depends on the diameter and [44] influenced by location, climate, and rainfall type [44]. Therefore, the coefficient can be obtained from the power laws developed based on empirically available DSD expressed by many researchers. In Table 1, the maximum (, ) and minimum (, ) kinetic energy equations which show > 30% difference from the calculated rainfall kinetic energies are excluded from regression analysis of empirical power laws. The linear regression equation (, ) from reliable power law is shown as in Figure 1. The coefficient was 10.3 when the exponent () for ideal power law was substituted in the linear regression equation (). Thus, the power law of timespecific rainfall kinetic energy by ideal assumption is proposed as follows:
4. Evaluations and Discussions
We compared the relationship between existing empirical equations and the ideal equation of rainfall power to evaluate the availability as the universal power law.
The average value of rainfall energies calculated by 13 exponential functions [4, 17, 24, 28, 30–34] presented in Table 1 was fitted with the result simulated by the ideal power law of rainfall power (, ) in Figure 2(a). The rainfall energy calculated by the ideal power law was distributed within the range of standard deviation of exponential functions. In case of rainfall intensity < 80 mm/h, the average value by exponential functions was greater than that of ideal power law while ideal power law had relatively greater rainfall energy after mm/h as the exponential function converges to the limited value in higher rainfall intensity [3, 25].
(a)
(b)
(c)
(d)
Comparison between the ideal equation and 8 logarithmic functions [3, 13, 28, 34–37] is presented in Figure 2(b). The average energy by logarithmic functions was relatively greater than that of the ideal power law; however, the relative difference was minor.
In case of linear functions with the lowest utilization as an equation of rainfall kinetic energy, the average energy by the linear functions [24, 28, 38–40] became smaller than that of the ideal equation at mm/h, and the relative difference was largest compared to other functions at the maximum rainfall intensity (150 mm/h) (Figure 2(c)).
The rainfall energy simulated by the ideal power law and the average rainfall energy calculated from power laws [26, 28, 29, 33, 41, 42] showed the greatest deviation of rainfall kinetic energy as shown in Figure 2(d). The average energy calculated by 14 power laws excluding the maximum and minimum kinetic energy equations shown in Table 1 is approximated to the values from the ideal power law. The mean exponent and coefficient deduced from existing power laws were and , respectively, which coincide approximately with the exponent 11/9 and coefficient 10.3 of the ideal power law indicating universal power law.
To utilize the universal power law as an erosivity factor of soil erosion models, it is necessary to conduct a comparative review throughout various rainfall kinetic energy equations used in existing soil erosion models. USLE [13] and EUROSEM [15] used logarithmic functions presented by Wischmeier and Smith [13] and Brandt [19], respectively, and RUSLE [14] and SEMMA [16] used exponential functions developed by Brown and Foster [17] and Van Dijk et al. [20], respectively. Comparison of results simulated from these equations and ideal power law is shown in Figure 3. The simulation results showed that universal power law appears closer to logarithmic function of Wischmeier and Smith [13]. With mm/h, its calculation was found to be greater than other equations. However, the relative difference with these rainfall energy equations showed reasonable value (4.8%).
The logarithmic, exponential, and powerlaw functions of the rainfall kinetic energies calculated by continuous DSD measurement data were presented by Kim et al. [42], Lim et al. [33], and Lee and Won [34] in South Korea’s representative sites. The rainfall kinetic energies simulated from those equations and universal power law are shown in Figure 4. The results simulated from power law by Lim et al. [33] and exponential and logarithmic functions by Lee and Won [34] showed relatively small difference as compared with the values calculated by universal power law.
Comparison of the average rainfall kinetic energies between various empirical equations and the universal equation was conducted to evaluate whether the universal power law can be used as a representative power law of erosivity factor on soil erosion. The relative difference between the rainfall kinetic energies was calculated in range of 20 mm/h mm/h (Table 2). The relative difference was most significant in case of a linear function at mm/h while mm/h; the energy of universal power law was found to be relatively greater. Power law showed the smallest relative difference which had the average relative difference of 0.06%. Moreover, exponential function used frequently in soil erosion models had small average relative difference (0.32%). Many studies confirmed that there is the maximum value of rainfall kinetic energy and determined that the exponential function with upper limit better describes the relationship between rainfall kinetic energy and rainfall intensity as compared to logarithmic, linear, and powerlaw functions with no upper limit [3, 17, 21–25]. In addition, Van Dijk et al. [20] proposed a general exponential equation based on comprehensive measurement data by reviewing literature. Actually, the kinetic energy of freefalling raindrops has the upper limit due to limited maximum size of raindrop in the order of 6–8 mm [2, 10, 52]. However, power law simulated excessively in high rainfall intensity may be more useful than exponential function in evaluating soil erosion because sediment transport capacity of running water increases with the rainfall kinetic energy. Interrill erosion model linked to powerlaw relationship with rainfall intensity has been adopted that the exponent of power law was approximated by ≥2 [54–56]. Therefore, the universal power law that used ideal assumption would take great advantages in utilization as erosivity factor to determine a quantitative assessment of soil erosion.

5. Conclusion
The empirical rainfall kinetic energy equations determined by the characteristics of the DSD have a variety of functional forms. In case of power laws, especially, the relative deviations of calculated energies depend on the exponents and coefficients of power laws. This study proposed a representative power law. The timespecific rainfall kinetic energy equation based on the power theory was derived through the ideal assumption that the dropsize is uniformly distributed under the constant rainfall intensity. The exponent of ideal power law was 11/9, and the coefficient was 10.3 which obtained from the relationship between exponents and coefficients of existing empirical power laws. The rainfall energy calculated by ideal equation was compared with results simulated by existing exponential, logarithmic, linear, and powerlaw functions. The logarithmic function showed the smallest deviation as compared to the ideal power law. The ideal equation in mm/h overestimated in comparison with exponential and linear functions. The mean rainfall kinetic energy calculated from empirical power laws corresponded approximately with the results of ideal power law. This supports that the ideal equation can be a universal form of the power law. The universal power law in comparison with rainfall kinetic energy equations used in typical soil erosion models showed that the relative difference was within 5%, and there was no significant deviation in relationship with equations of rainfall kinetic energy presented by DSD measurement. It was also confirmed that the relative differences in the average rainfall kinetic energy between various empirical equations and universal equation of rainfall power law were not significant. These results prove that the universal power law can represent the existing empirical power laws. There was a trend that the kinetic energy by universal power law had relatively overestimated as compared to other empirical equations in mm/h. However, this result supports the conclusion that it can be more useful in the development of soil erosion models due to significant increase in sediment yield by increasing transport capacity of surface runoff in the high rainfall intensity ( mm/h).
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
Acknowledgment
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (no. 2013R1A1A3011962).
References
 M. J. Hall, “Use of the stain method in determining the drop size distribution of coarse liquid sprays,” Transactions of the American Society of Agricultural Engineers, vol. 13, pp. 33–37, 1970. View at: Google Scholar
 J. O. Laws and D. A. Parsons, “The relation of raindrop size to intensity,” Transactions of the American Geophysical Union, vol. 26, pp. 452–460, 1943. View at: Google Scholar
 P. I. A. Kinnell, “Rainfall intensitykinetic energy relationships for soil loss prediction,” Soil Science Society of America Journal, vol. 45, no. 1, pp. 153–155, 1981. View at: Publisher Site  Google Scholar
 G. F. McIsaac, “Apparent geographic and atmospheric influences on raindrop sizes and rainfall kinetic energy,” Journal of Soil & Water Conservation, vol. 45, no. 6, pp. 663–666, 1990. View at: Google Scholar
 T.I. Wang, K. B. Earnshaw, and R. S. Lawrence, “Pathaveraged measurements of rain rate and raindrop size distribution using a fastresponse optical sensor,” Journal of Applied Meteorology, vol. 18, no. 5, pp. 654–660, 1979. View at: Publisher Site  Google Scholar
 A. J. Illingworth and C. J. Stevens, “An optical disdrometer for the measurement of raindrop size spectra in windy conditions,” Journal of Atmospheric and Oceanic Technology, vol. 4, no. 3, pp. 411–421, 1987. View at: Publisher Site  Google Scholar
 C. Salles and J. Poesen, “Performance of an optical spectro pluviometer in measuring basic rain erosivity characteristics,” Journal of Hydrology, vol. 218, no. 34, pp. 142–156, 1999. View at: Publisher Site  Google Scholar
 J. O. Laws, “Measurements of the fallvelocity of waterdrops and raindrops,” Eos, Transactions American Geophysical Union, vol. 22, pp. 709–721, 1941. View at: Publisher Site  Google Scholar
 R. Gunn and G. D. Kinzer, “The terminal velocity of fall for water droplets in stagnant air,” Journal of Meteorology, vol. 6, no. 4, pp. 243–248, 1949. View at: Publisher Site  Google Scholar
 K. V. Beard, “Terminal velocity and shape of cloud and precipitation drops aloft,” Journal of the Atmospheric Sciences, vol. 33, no. 5, pp. 851–864, 1976. View at: Google Scholar
 N. W. Hudson, “An intorduction to the mechanics of soil erosion under conditions of subtropical rainfall,” Transactions of the Rhodesia Scientific Association, vol. 49, pp. 15–25, 1961. View at: Google Scholar
 A. W. Jayawardena and R. B. Rezaur, “Measuring drop size distribution and kinetic energy of rainfall using a force transducer,” Hydrological Processes, vol. 14, no. 1, pp. 37–49, 2000. View at: Publisher Site  Google Scholar
 W. H. Wischmeier and D. D. Smith, “Rainfall energy and its relationship to soil loss,” Transactions of the American Geophysical Union, vol. 39, no. 2, pp. 285–291, 1958. View at: Publisher Site  Google Scholar
 K. G. Renard, G. R. Foster, G. A. Weesies, D. K. McCool, and D. C. Yoder, “Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Epuation (RUSLE),” in US Department of Agriculture Handbook 703, US Department of Agriculture, Agricultural Search Service, Washington, DC, USA, 1997. View at: Google Scholar
 R. P. C. Morgan, J. N. Quinton, R. E. Smith et al., “The European soil erosion model (EUROSEM): a dynamic approach for predicting sediment transport from fields and small catchments,” Earth Surface Processes and Landforms, vol. 23, no. 6, pp. 527–544, 1998. View at: Publisher Site  Google Scholar
 S. D. Park, K. S. Lee, and S. S. Shin, “A statistical soil erosion model for burnt mountain areas in Korea—RUSLE approach,” Journal of Hydrologic Engineering, vol. 17, no. 2, pp. 292–304, 2012. View at: Publisher Site  Google Scholar
 L. C. Brown and G. R. Foster, “Storm erosivity using idealized intensity distributions,” Transactions of the American Society of Agricultural Engineers, vol. 30, no. 2, pp. 379–386, 1987. View at: Publisher Site  Google Scholar
 J. S. Marshall and W. M. Palmer, “The distribution of raindrop with size,” Journal of Meteorology, vol. 5, pp. 165–166, 1948. View at: Google Scholar
 C. J. Brandt, “The size distribution of throughfall drops under vegetation canopies,” CATENA, vol. 16, no. 45, pp. 507–524, 1989. View at: Publisher Site  Google Scholar
 A. I. J. M. Van Dijk, L. A. Bruijnzeel, and C. J. Rosewell, “Rainfall intensitykinetic energy relationships: a critical literature appraisal,” Journal of Hydrology, vol. 261, no. 1–4, pp. 1–23, 2002. View at: Publisher Site  Google Scholar
 N. W. Hudson, “Raindrop size distribution in high intensity storms,” Rhodesian Journal of Agricultural Research, vol. 1, pp. 6–11, 1963. View at: Google Scholar
 P. C. Baruah, An investigation of drop size distribution of rainfall in Thailand [M.S. thesis], Asian Institute of Technology, Bangkok, Thailand, 1973.
 C. E. Carter, J. D. Greer, H. J. Braud, and J. M. Floyd, “Raindrop characteristics in south central United States,” Transactions of the American Society of Agricultural Engineers, vol. 17, no. 6, pp. 1033–1037, 1974. View at: Publisher Site  Google Scholar
 C. J. Rosewell, “Rainfall kinetic energy in eastern Australia,” Journal of Climate & Applied Meteorology, vol. 25, no. 11, pp. 1695–1701, 1986. View at: Publisher Site  Google Scholar
 W. H. Wischmeier and D. D. Smith, “Predicting rainfall erosion losses,” in Agriculture Handbook No. 537, U.S. Department of Agriculture, Washington, DC, USA, 1978. View at: Google Scholar
 J. A. Smith and R. D. de Veaux, “The temporal and spatial variability of rainfall power,” Environmetrics, vol. 3, no. 1, pp. 29–53, 1992. View at: Publisher Site  Google Scholar
 C. Salles, J. Poesen, and D. SempereTorres, “Kinetic energy of rain and its functional relationship with intensity,” Journal of Hydrology, vol. 257, no. 1–4, pp. 256–270, 2002. View at: Publisher Site  Google Scholar
 R. L. Fornis, H. R. Vermeulen, and J. D. Nieuwenhuis, “Kinetic energyrainfall intensity relationship for Central Cebu, Philippines for soil erosion studies,” Journal of Hydrology, vol. 300, no. 1–4, pp. 20–32, 2005. View at: Publisher Site  Google Scholar
 R. Uijlenhoet and J. N. M. Stricker, “A consistent rainfall parameterization based on the exponential raindrop size distribution,” Journal of Hydrology, vol. 218, no. 34, pp. 101–127, 1999. View at: Publisher Site  Google Scholar
 D. C. Blanchard, “Raindrop sizedistribution in Hawaiian rains,” Journal of Meteorology, vol. 10, no. 6, pp. 457–473, 1953. View at: Publisher Site  Google Scholar
 M. Azevedo Coutinho and P. Pereira Tomás, “Characterization of raindrop size distributions at the Vale Formoso Experimental Erosion Center,” CATENA, vol. 25, no. 1–4, pp. 187–197, 1995. View at: Publisher Site  Google Scholar
 A. W. Jayawardena and R. B. Rezaur, “Drop size distribution and kinetic energy load of rainstorms in Hong Kong,” Hydrological Processes, vol. 14, no. 6, pp. 1069–1082, 2000. View at: Publisher Site  Google Scholar
 Y. S. Lim, J. W. Kim, J. K. Kim, and B. I. Park, “Evaluation of kinetic energy of raindrops at Daejeon city using laseroptical disdrometer,” Journal of the Korean Geomorphological Association, vol. 19, no. 2, pp. 133–143, 2012. View at: Google Scholar
 J. S. Lee and J. Y. Won, “Analysis of the characteristic of monthly rainfall erosivity in Korea with derivation of rainfall energy equation,” Journal of Korean Society of Hazard Mitigation, vol. 13, no. 3, pp. 177–184, 2013. View at: Publisher Site  Google Scholar
 K. Onaga, K. Shirai, and A. Yoshinaga, “Rainfall erosion and how to control its effects on farmland in Okinawa,” in Land Conservation for Future Generation, S. Rimwanich, Ed., pp. 627–639, Department of Land Development, Bangkok, Thailand, 1988. View at: Google Scholar
 C. Zanchi and D. Torri, “Evaluation of rainfall energy in central Italy,” in Assessment of Erosion, M. de Boodt and D. Gabriels, Eds., pp. 133–142, Wiley, Toronto, Canada, 1980. View at: Google Scholar
 C. J. Brandt, “Simulation of the size distribution and erosivity of raindrops and throughfall drops,” Earth Surface Processes & Landforms, vol. 15, no. 8, pp. 687–698, 1990. View at: Publisher Site  Google Scholar
 N. W. Hudson, The influence of rainfall mechanics on soil erosion [MSc. thesis], Cape Town University, Cape Town, South Africa, 1965.
 D. SempereTorres, C. Salles, J. D. Creutin, and G. Delrieu, “Quantification of soil detachment by raindrop impact: performance of classical formulae of kinetic energy in Mediterranean storms. Erosion and sediment transport monitoring programs in river basin,” IASH Publications, vol. 210, pp. 115–124, 1992. View at: Google Scholar
 A. Usón and M. C. Ramos, “An improved rainfall erosivity index obtained from experimental interrill soil losses in soils with a mediterranean climate,” CATENA, vol. 43, no. 4, pp. 293–305, 2001. View at: Publisher Site  Google Scholar
 M. Steiner and J. A. Smith, “Reflectivity, rain rate, and kinetic energy flux relationships based on raindrop spectra,” Journal of Applied Meteorology, vol. 39, no. 11, pp. 1923–1940, 2000. View at: Publisher Site  Google Scholar
 J. K. Kim, D. Y. Yang, and M. S. Kim, “Evaluating physical characteristics of raindrop in Anseong Gyeonggi province,” Journal of the Korean Geomorphological Association, vol. 17, no. 1, pp. 49–57, 2010. View at: Google Scholar
 P. I. A. Kinnell, “The problem of assessing the erosive power of rainfall from meteorological observations,” Soil Science Society of America, vol. 37, no. 4, pp. 617–621, 1973. View at: Publisher Site  Google Scholar
 D. S. Torres, J. M. Porrà, and J. D. Creutin, “A general formulation for raindrop size distribution,” Journal of Applied Meteorology, vol. 33, no. 12, pp. 1494–1502, 1994. View at: Google Scholar
 L. V. Madden, L. L. Wilson, and N. Ntahimpera, “Calibration and evaluation of an electronic sensor for rainfall kinetic energy,” Phytopathology, vol. 88, no. 9, pp. 950–959, 1998. View at: Publisher Site  Google Scholar
 D. SempereTorres, J. M. Porrà, and J.D. Creutin, “Experimental evidence of a general description for raindrop size distribution properties,” Journal of Geophysical Research D: Atmospheres, vol. 103, no. 2, pp. 1785–1797, 1998. View at: Publisher Site  Google Scholar
 A. C. Best, “The size distribution of raindrops,” Quarterly Journal of The Royal Meteorological Society, vol. 76, pp. 16–36, 1950. View at: Google Scholar
 C. W. Ulbrich, “Natural variations in the analytical form of the raindrop size distribution,” Journal of Climate & Applied Meteorology, vol. 22, no. 10, pp. 1764–1775, 1983. View at: Publisher Site  Google Scholar
 G. Feingold and Z. Levin, “The lognormal fit to raindrop spectra from frontal convective clouds in Israel,” Journal of Climate & Applied Meteorology, vol. 25, no. 10, pp. 1346–1363, 1986. View at: Publisher Site  Google Scholar
 D. Atlas and C. W. Ulbrich, “Path and areaintegrated rainfall measurement by microwave attenuation in the 13cm band,” Journal of Applied Meteorology, vol. 16, pp. 1322–1331, 1977. View at: Google Scholar
 C. Salles, D. SempereTorres, and J. D. Creutin, “Characterisation of raindrop size distribution in Mediterranean climate: analysis of the variations on the ZR relationship,” in Proceedings of the 29th Conference on Rada Meteorology, pp. 671–673, AMS, Montreal, Canada, July 1999. View at: Google Scholar
 J. Joss and A. Waldvogel, “Raindrop size distribution and sampling size errors,” Journal of the Atmospheric Sciences, vol. 26, no. 3, pp. 566–569, 1969. View at: Google Scholar
 G. Zhou, X. Wei, and J. Yan, “Impacts of eucalyptus (Eucalyptus exserta) plantation on sediment yield in Guangdong Province, Southern Chin—a kinetic energy approach,” CATENA, vol. 49, no. 3, pp. 231–251, 2002. View at: Publisher Site  Google Scholar
 L. D. Meyer, “How rain intensity affects rill erosion,” Transaction American Society of Agricultural Engineers, vol. 24, no. 6, pp. 1472–1475, 1981. View at: Publisher Site  Google Scholar
 C. C. Truman and J. M. Bradford, “Relationships between rainfall intensity and the interrill soil lossslope steepness ratio as affected by antecedent water content,” Soil Science, vol. 156, no. 6, pp. 405–413, 1993. View at: Publisher Site  Google Scholar
 A. J. Parsons and P. M. Stone, “Effects of intrastorm variations in rainfall intensity on interrill runoff and erosion,” CATENA, vol. 67, no. 1, pp. 68–78, 2006. View at: Publisher Site  Google Scholar
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Copyright © 2016 Seung Sook Shin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.