• Journal of the Korean GEO-environmental Society
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• v.19 no.12
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• pp.15-23
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• 2018

The occurrence of soil erosions in Korea is mostly driven by flowing water which has a close relationship with rainfalls. The soil eroded by rainfalls flows into and deposits in the river and it polluted the water resources and making the rivers become difficult to be managed. Recently, the frequency of heavy rainfall events that are more than 30 mm/hr has been increasing in Korea due to the influence of climate change, which creating a favourable condition for the occurrence of soil erosion within a short time. In this study, we proposed a method to estimate the distribution of rainfall intensity and to calculate the energy produced by a single rainfall event using the cumulative distribution function that take into account of the physical characteristics of rainfall. The raindrops kinetic energy estimated by the proposed method are compared with the measured data from the previous studies and it is noticed that the raindrops kinetic energy estimated by the rainfall intensity variation is very similar to the results concluded from the previous studies. In order to develop an equation for estimating rainfall kinetic energy, rainfall particle size data measured at a rainfall intensity of 0.254~152.4 mm/hr were used. The rainfall kinetic energy estimated by applying the cumulative distribution function tended to increase in the form of a power function in the relation of rainfall intensity. Based on the equation obtained from this relationship, the rainfall kinetic energy of 1~80 mm/hr rainfall intensity was estimated to be $0.03{\sim}48.26Jm^{-2}mm^{-1}$. Based on the relationship between rainfall intensity and rainfall energy, rainfall kinetic energy equation is proposed as a power function form and it is expected that it can be used in the design of short-term operated facility such as the sizing of sedimentation basin that requires prediction of soil loss by a single rainfall event.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.111-118
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• 2020

The rainfall kinetic energy equation derived in the USA has been used in South Korea to quantitatively estimate the amount of soil erosion caused by rainfall for the past 40 years. It is critical to analyze the characteristics of rainfall kinetic energy that causes soil erosion from measured storm events in the study area because the characteristics depend on climate, region, and time. The purpose of this study is to analyze the characteristics in Seoul, South Korea, and the data of the Parsivel rain gauge measured in Seoul for 3 years was used for the current study. This study focuses on deriving the relationship between rainfall kinetic energy and rainfall intensity among the data measured by the Parsivel. The new rainfall kinetic energy equation in Seoul is proposed and compared with the previous equations used in South Korea.

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.603-610
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• 2000

Climate factors such as rainfall, temperature, wind, humidity, and solar radiant heat affect soil erosion. Among those factors, rainfall influences soil erosion to the most extent. The kinetic energy of rainfall breaks away soil particles and the water flow caused by the rainfall entrains and transport them downstream. In order to estimate soil erosion, therefore, it is important to determine the rainfall erosivity. In this study, the annual average Rainfall Erosivity(R) in Korea, an important factor of the Universal Soil Loss Equation(USLE) and Revised Equation(RUSLE), has been estimated using the nationwide rainfall data from 1973 to 1996. For this estimation, hourly rainfall data at 53 meterological stations managed by the Meterological Agency was used. It has been found from this study that the newly computed values for R are slightly larger than the existing ones. It would be because this study is based on the range of rainfall data that is longer in period and denser in the number of gauging stations than what the existing result used. The final result of this study is shown in the form the isoerodent map of Korea.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.559-568
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• 2013

Surface compaction significantly impacts runoff and soil erosion under rainfall since it leads to changes of soil physical characteristics such as increase of bulk density and shear stress, change of microporosity, and decrease of hydraulic conductivity. This study addressed surface compaction effects on runoff and soil loss from bare and disturbed soils that are commonly distributed on construction sites. Thirty-six rainfall simulations from three replicates of each involving rainfall intensities (68.5 mm/hr, 95.6 mm/hr) and plot gradients ($5^{\circ}$, $12.5^{\circ}$, $20^{\circ}$) were conducted to measure runoff and soil loss for two different soil surface treatments (compacted surface, non-compacted surface). Compacted surface increased significantly soil bulk density and soil strength. However, the effect of surface treatments on runoff changed with rainfall intensity and plot gradient. Rainfall intensity and plot gradient had a positive effect on mean soil loss. In addition, the effect of surface treatments on soil loss responded differently with rainfall intensity and plot gradient. Compacted surfaces increased soil loss at gentle slope ($5^{\circ}$) while they decreased soil loss at steep slope ($20^{\circ}$). These results indicate that there exists transitional slope range ($10{\sim}15^{\circ}$) between gentle and steep slope by surface compaction effects on soil loss under disturbed bare soils and simulated rainfalls.

• Journal of Korean Society of Forest Science
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• v.29 no.1
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• pp.54-101
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• 1976

This study was conducted on the major factors affecting soil erosion and surface run-off. In order to investigate the processes and mechanisms of soil erosion on denuded forest-land in Korea, and to systematize the magnitudes of influences and interactions between individual factors, the five major factors adopted in these experiments are soil textures (coarse sand and clay loam), slope steepness ($10^{\circ}$, $20^{\circ}$, $30^{\circ}$ and $40^{\circ}$), rainfall intensities (50, 75 and 100mm/hr), slope mulching methods (bare, coarse straw-mat mulching, grass mulching and anti-erosion liquid mulching) and vegetation densities (sparse, moderate and dense). The processes and mechanisms of soil erosion, and the effects of mulchings on soil erosion as well as surface run-off rates were studied algebraically with four parts of laboratory experiments under the simulated rainfall and another part of field experiment under the natural rainfall. The results in this study are summarized as follows: 1. Experiment factors and surface run-off rates The surface run-off rates under the natural rainfall were resulted about 24.7~28.7% from the bare slopes, about 14.0~16.4% from the straw-mat mulched slopes, about 7.9~9.1% from the liquid mulched slopes, and about 5.6~7.2% from the grass mulched slopes respectively. The surface run-off rates under the simulated rainfall differed greatly according to the rainfall intensity and the mulching method. 2. Magnitudes of influences and interactions of the individual factor on the surface run-off rates. The experimental analyses on the major factors(soils, slopes, rainfalls, mulchings and vegetations) affecting the rates of surface run-off, show that the mean differences of surface run-off rate are significant at 5% level between the soil texture factors, among the slope steepness factors, among the rainfall intensity factors, among the mulching method factors, and among the vegetation density factors respectively. The interactions among the individual factor have a great influence(significant at 1% level) upon the rate of surface run-off, except for the interactions of the factors between soils and slopes; between slopes and vegetations; among soils, slopes and rainfalls; and among soils, slopes and mulchings respectively. On the bare slopes under the simulated rainfall, the magnitude of influences of three factors(soils, slopes and rainfalls) affecting the rate of surface run-off is in the order of the factor of rainfalls, soils and slopes. The magnitude of influences of three factors (soils, rainfalls and mulchings) affecting the rate of surface run-off, on the mulched slopes under the simulated rainfall is in the order of the factor of mulchings, rainfalls and soils and that of influences of the factor of soils, slopes and mulchings is in the order of the factor of mulchings, soils and slopes. On the vegetation growing slopes under the simulated rainfall, the magnitude of influences of three factors (soils, slopes and vegetations) affecting the rate of surface run-off is in the order of the factor of vegetations, soils and slopes. In the same condition of treatments on the field experiment under the natural rainfall, the order of magnitude of influences affecting the rate of surface run-off is the factor of mulchings, soils and slopes. 3. Experiment factors and soil losses The soil losses of the experiment plots differed according to the factors of soil texture, slope steepness, rainfall intensity and mulching method. The soil losses from the coarse soil were increased about 1.1~1.3 times as compared with that of fine soil under the natural rainfall, while the soil losses from the fine soil were increased about 1.2~1.3 times compared with that of coarse soil under the simulated rainfall. The equation of $E=aS^b$ (a, b are constant) between the slope steepness (log S) and soil losses (log E) under the simulated rainfall were developed. The equation of $E=aI^b$ (a, b are constant) between the rainfall intensity (log I) and soil losses (log E) were developed, and b values have a decreasing tendency according to the increase of the slope steepness and rainfall intensity. The soil losses under the natural rainfall were appeared about 38~41% from the coarse straw-mat mulched slopes, about 20~22% from the liquid mulched slopes, about 14~15% from the grass mulched slopes as compared with that of the bare slopes respectively. The soil loss from the vegetation plots showed about 7.1~16.4 times from the sparse plot, about 10.0~17.9 times from the moderate plot and about 11.1~28.1 times from the dense plot as compared with that of the bare slopes. 4. Magnitudes of influences and interactions of the individual factor on the soil erosion. The experimental analyses on the major factors(soils, slopes, rainfalls, mulchings and vegetations) affecting the soil erosion, show that the mean differences of soil losses are highly significant between the soil texture factors, among the slope steepness factors, among the rainfall intensity factors, among the mulching method factors and among the vegetation density factors respectively. The interactions among the individual factor have mostly great influences upon the soil erosion. The magnitude of influences of three factors (soils, slopes and rainfalls) affecting the soil erosion on the bare slopes under the simulated rainfall is in order of the factor of rainfalls, soils and slopes. On the mulched slopes under the simulated rainfall, the magnitude order of influences of three factors(soils, rainfalls and mulchings) affecting the soil erosion is the factor of mulchings, rainfalls and soils, and the order of influences of factor of soils, slopes and mulchings is the factor of mulchings, soils and slopes. On the vegetation growing slopes under the simulated rainfall, the magnitude of influences of three factors (soils, slopes and vegetations) affecting the soil erosion is in the order of the factor of slopes. vegetations and soils. In the same condition of treatments on the field experiment under the natural rainfall, the order of magnitude of influences of three factors (soils, slopes and mulchings) affecting the soil erosion is the factor of mulchings, of slopes and of soils.

• Spatial Information Research
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• v.17 no.4
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• pp.431-443
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• 2009

Recently, turbidity problem is one of the hot issues in dam and reservoir management works. Main reason to bring about high density turbid water is sediment yield by rainfall intensity energy. Because existing researches didn't consider diverse types of crops, it was difficult to calculate more accurate soil erosion and sediment yield. This study was evaluated the reduction efficiency of soil erosion and sediment yield using ginseng layer extracted from IKONOS satellite image, and the area and the ratio of ginseng area represented $0.290km^2$ and 0.94%. The reduction efficiency of soil erosion considering ginseng area represented low value in 0.9% using GIS-based RUSLE model, because the area of ginseng was small compared to areas of other agricultural lands. To reflect future land use change, this study was calculated the reduction efficiency of soil erosion and sediment yield by considering many scenarios as kinds of crops of paddy, dry field, orchard, and other agricultural areas convert to the ginseng district. As result of analysis of them according to scenarios, scenario (1) in which dry field was converted to ginseng area and scenario (2) in which fully agricultural lands were converted to ginseng area showed high reduction efficiency as 31.3% and 34.8% respectively, compared to existing research which didn't consider ginseng area. Methodology suggested in this study will be very efficient tools to help reservoir management related to high density turbid water.

• Journal of Korea Water Resources Association
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• v.41 no.6
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• pp.565-574
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• 2008

Fire-enhanced soil hydrophobicity often increases runoff and erosion in the mountain hillslope following severe wildfires. Estimation techniques for WEPP's parameters were studied in burnt mountain slopes. In burnt mountain slopes, the model over-predicted runoff in the small runoff and under-predicted runoff in the great runoff, and in the lower sediment runoff it had a tendency to over-predict soil loss. The effective hydraulic conductivity was most sensitive in the WEPP's runoff and its sediment runoff was mainly effected by the effective hydraulic conductivity, initial saturation, rill erodibility, and interrill erodibility. To improve the applicability of the WEPP, the adjustment coefficient of effective hydraulic conductivity was defined for runoff and the adjustment coefficient of rill erodibility and interrill erodibility was presented for sediment runoff. The adjustment coefficient of effective hydraulic conductivity in wildfire mountain slopes increased with maximum rainfall intensity of single storm and the vegetation height index. The adjustment coefficients of rill erodibility depended on soil components of size distribution curve and total rainfall depths in single storm. The adjustment coefficients of interrill erodibility decreased with increases of maximum rainfall intensity and vegetation height index. These results may be used in the application of WEPP model for wildfire mountain slopes.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.151-151
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• 2022

The impact of raindrops on the soil surface causes soil detachment, which may be estimated by measuring the kinetic energy (KE) of the raindrops. Since direct measurements of rainfall force on ground surfaces are not generally available, empirical equations are an alternative option to estimate KE from rainfall intensity (I), which has the greatest influence over soil erosion and is easily accessible. Establishing the optimal formulation for the relationship between kinetic energy and rainfall intensity has proven to be difficult. Thus, this research considered thirty-seven rainfall events observed from June 2020 to December 2021 using a laster optical disdrometer erected in Kyungpook National University to examine the characteristics of KE-I relationships. We concentrated our discussion on the formation of two different expressions of the KE, including KE expenditure (KE_exp) and KE content (KE_con). The following conclusions were drawn: (1) We employed statistical analysis to demonstrate that the KE_exp is more suitable expression for establishing an empirical rule between KE and I than the KE_con. (2) A power-law model was used to find the best correlation between KE_exp-I relationship, whereas the best match between KE_con and I were found using an exponential equation.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.877-881
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• 2012

This research was carried out to investigate the interaction effect of slope gradient and rainfall intensity on soil loss with rainfall simulator. The soils used in this experiment were saprolite, Chahang series which distributed extensively in Daegwanryong. Slope gradient applied was 0.5, 7, 15 and 30%. Rainfall intensity applied was 20, 60 and $90mm\;hr^{-1}$. The result obtained can be summarised as follow; Overall, Chahang series suffered more losses than saprolite. Chahang series shows the immediately large increase of soil loss with the increasing soil gradient and rainfall intensity. However, saprolite shows a little increasing loss up to 7% gradient and abruptly increasing loss logarithmically over 7% gradient in soil slope. In combination of slope gradient 15, 30% and rainfall intensity 60, $90mm\;hr^{-1}$ processing, both soil erosion happened significantly. And there was no significant difference between the two soils. Because Chahang series have the danger of soil loss with low slope gradient and rainfall intensity, we should give greater attention to soil management in Chahang series.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.371-378
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• 2020

Rainfall is one of the most active forces that cause soil erosion. The action of rain on the soil exerts an erosive power caused by the impact of the drops, which fall with variable speed and kinetic energy, depending directly on the diameter of the drop. The objective of this study is to determine algorithms capable of estimating rainfall erosivity for the region of Maceió-AL. For this purpose, erosion rains were collected between 2003 and 2006 using a RD-69 disdrometer, which continuously and automatically measures rainfall distribution in a range of 1 min. The determination of algorithms in the form of power equation to estimate was adjusted with one and two independent variables (amount of rainfall, duration and maximum intensity).