• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.3
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• pp.29-40
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• 2003

The objective of the paper is to compute the half-month rainfall-runoff erosivity factor for revised universal soil loss equation (RUSLE). RUSLE is being used to develop soil conservation programs and identify optimum management practices. Rainfall-runoff erosivity factor (R) is a key input parameter to RUSLE. Rainfall-runoff erosivity factor has been calculated for twenty six stations from the nationwide rainfall data from 1973 to 2002 in south Korea. The average annual Rainfall-runoff erosivity factor at the analyzed stations Is between 3,130 and 10,476 (MJ/ha)ㆍ(mm/h). According to the computation of the half-month Rainfall-runoff erosivity factor for locations, 66-85% of the average annual R value has occurred during the summer months, June-August. The half-month R values from this study can be used for RUSLE.

• Journal of Korean Society of Water and Wastewater
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• v.30 no.1
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• pp.51-58
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• 2016

On account of the increase in water demand and climate change, droughts are in great concern for water resources planning and management. In this study, rainfall characteristics with stationary and non-stationary perspectives were analyzed using Weibull distribution model with 40-year records of annual minimum rainfall depth collected in major cities of Korea. As a result, the non-stationary minimum probable rainfall was expected to decrease, compared with the stationary probable rainfall. The reliability of ${\xi}_1$, a variable reflecting the decrease of the minimum rainfall depth due to climate change, in Wonju, Daegu, and Busan was over 90%, indicating the probability that the minimal rainfall depths in those city decrease is high.

• Journal of Environmental Science International
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• v.2 no.3
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• pp.179-191
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• 1993

This paper aims to know the characteristics of occurrence of the anomaly level and variability of the monthly precipitation in Kyeongnam, Korea. For this study, it was investigated 주e distribution of the annual and cont비y mean precipitation, the precipitation variability and its annual change, and the characteristics of occurrence of the anomaly level in Kyeongnam area the results were summarized as follows : 1) she mean of annual total precipitation averaged over Kyeongnam area is 1433.3mm. I'he spatial distribution of the annual total precipitation shows that in Kyeongnam area, the high rainfall area locates in the southwest area and south coast and the low rainfall area in an inland area. 2) Monthly mean precipitation in llyeongnam area was the highest in July(266.4mm) 각lowed by August(238.0mm), June(210.2mm) in descending order. In summer season, rainfall was concentrated and accounted for 49.9 percent of the annual total precipitation. Because convergence of the warm and humid southwest current which was influenced by Changma and typhoon took place well in this area. 3) The patterns of annual change of precipitaion variability can be divided into two types; One is a coast type and the other an inland type. The variability of precipitation generally appears low in spring and summer season and high in autumn and winter season. This is in accord with the large and small of precipitation. 4) The high frequency of anomaly level was N( Normal)-level and the next was LN( Low Informal) -level and 25(Extremely Subnormal)-level was not appeared in all stations. The occurrence frequency of N level was high in high rainfall area and distinguish성 in spring and summer season but the low rainfall area was not. hey Words : anomaly level, variability, precipitation, coast type, inland type.

• Journal of Korean Society on Water Environment
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• v.26 no.4
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• pp.648-653
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• 2010

Discharged pollution load for the management of Total Maximum Daily Loads (TMDLs) is calculated on the basis of rainfall data for reference year. Rainfall has an influence on discharged pollution load in unit watershed with combined sewer system. This study reviewed the status of discharged pollution load and rainfall conditions. We also investigated rainfall effects on discharged pollution load by analyzing change of the load in accordance with increase of rainfall. The change ratio of discharged pollution load was 18.6% while inflow load only 5.8% for 5 years from 2004 to 2008 in Daejeon district. The greatest rainfall and rain days were over 2 times than the least during the period. This change in rainfall could have great effect on discharged pollution load. The analysis showed that discharged pollution load increased 2.1 times in case rainfall increased 2 times and 1.2 times in case rain days increased 2 times. Rainfall effects, therefore, should be considered to make resonable evaluation of discharged pollution load in the assessment of annual performances.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.575-581
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• 2002

This study evaluates the variation of estimation error of area-average rainfall due to rainfall seasonality. Both the cases considering and not considering the spatial correlation are compared to derive the characteristics of estimation error. Similar cases with different accumulation time without considering the rainfall seasonality are also investigated. This study was applied to the Geum-river basin with total 28 rain gauge measurements haying more than 30 years of daily rainfall measurements. As results of the study we found that: (1) The absolute estimation error of monthly area-average rainfall show strong seasonality like the total rainfall amount. However, the relative estimation error normalized by its mean was estimated to have similar values about 5 to 8% except January and December. (2) The relative estimation error of annual area-average rainfall estimated was found to have the estimation error about 3% of its annual mean. (3) However, the relative estimation error normalized by the standard deviation remains almost the same for both monthly and annual rainfall amounts, which was estimated about 11% of its standard deviation. (4) Finally, the estimation error without considering the spatial correlation was found to become almost twice the estimation error with considering the spatial correlation.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.783-793
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• 2018

The purpose of this study to present updated regional annual mean rainfall erosivity data in the Republic of Korea. In 2012, Ministry of Environment in Korea published the notice about investigation and survey procedure for the amount of topsoil erosion and adopted USLE (Universal Soil Loss Equation) model to predict the amount of national-scale soil erosion in Korea. In the notice, regional rainfall erosivity values for 158 sites, which is essential to apply the USLE, were included, however, these values came from the data made before 1997 and need to be updated. This study collected, classified and combined annual mean rainfall erosivity data from the literature review to analyze the data. We presented that new iso-erodent map, interpolated by IDW (Inverse Distance Weighted) method and extracted updated regional annual mean rainfall erosivity data at 167 regions for 1961~2015. These values will be used as updated rainfall erosivity data to predict the amount of topsoil erosion in Korea.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.203-206
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• 1998

Since it has been very difficult to collect Korean rain data for winter season, e.g. from November to March, it would be very useful to design satellite communication links if there is a method to extract annual distribution from rain data collected for a specific month. This paper presents a conversion method to annual rainfall rate distribution from rain data for worst month of a year, and illustrates some analysis of the conversion results.

• Water for future
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• v.28 no.2
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• pp.145-154
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• 1995

The various analyses of the historical rainfall data need to be utilized in a hydraulic engineering project. The probability distributions of the rainfall events according to annual maximum continuous rainfall depths are studied for the hydrologic frequency analysis. The bivariate normal distribution, the bivariate lognormal distribution, and the bivariate gamma distribution are applied to the rainfall events composed of rainfall depths and its durations at Kangnung, Seoul, Incheon, Chupungnyung, Teagu, Jeonju, Kwangju, and Busan. These rainfall events are fitted to the the bivariate normal distribution and the bivariate lognormal distribution, but not fitted to the bivariate gamma distribution. Frequency curves of probability rainfall events are suggested from the probability distribution selected by the goodness-of-fit test.

• Current Research on Agriculture and Life Sciences
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• v.5
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• pp.143-157
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• 1987

In order to determine the design precipitation, the most probable daily precipitation and annual precipitation at every spot are calculated and iso - precipitation line are drawn. Probability of precipitation and drought phenomena of each gage station are analyzied by the method of frequency analysis from the statistical conceptions. The results summarized in this study are as the follows. 1. Annual mean precipitation in kyungpook area are 1044 mm, about 115 mm less than annual mean precipitation of Korea amounts to l1S9mm, and found to regionally unequal. 2. Monthly mean rainfall of July is 242.2mm, 23.2%, August 174.2mm, 16.7%, June 115mm, 11% and September 114.2mm, 10.9% and Rainfall depth of July-August are more than 40% of annual precipition. This shows notable summer rainy weather by typoon and low pressure storm and seasonal unbalance of water supply. 3. The relation among the maximum precipi.tation per day, per two continuous days and per three contnous days are caculated and the latter is found 31.0% increased rate of the first and the last 48.2% increased rate of first. 4. Probability precipitation in Kyungpook area are shown as 9.0%(5 year), 13.3%(10 year), 17.7%(20 year), 23.1%(50 year), 27.0%(100 year) and 31.1%(200 year) increased rate of each recurrence year compared with observed average annual precipitation. 5. From annual precipitation and maximum daily rainfall data probability of precipitation and precipitation isohyetal line are derived which shown as Table 11 and Fig. 8. 6. Drought days are divided 6 class and analysed results are shown on table 12. Average occurrence time of 10-14 continuous drought days are 2.3 time per year, 15-19 days are 0.9 time per year, 20-24 days are one per six years, 30-34 days are once per nine years and over than 35days are once per 25 years.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.260-260
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• 2016

Soil erosion is a very serious problem from agricultural as well as environmental point of view. Various computer models have been used to estimate soil erosion and assess erosion control practice. Universal Soil loss equation (USLE) is a popular model which has been used in many countries around the world. Erosivity (USLE R-factor) is one of the USLE input parameters to reflect impacts of rainfall in computing soil loss. Value of R factor depends upon Energy (E) and maximum rainfall intensity of specific period ($I30_{max}$) of that rainfall event and thus can be calculated using higher temporal resolution rainfall data such as 10 minute interval. But 10 minute interval rainfall data may not be available in every part of the world. In that case we can use hourly rainfall data to compute this R factor. Maximum 60 minute rainfall ($I60_{max}$) can be used instead of maximum 30 minute rainfall ($I30_{max}$) as suggested by USLE manual. But the value of Average annual R factor computed using hourly rainfall data needs some correction factor so that it can be used in USLE model. The objective of our study are to derive relation between averages annual R factor values using 10 minute interval and hourly rainfall data and to determine correction coefficient for R factor using hourly Rainfall data.75 weather stations of Korea were selected for our study. Ten minute interval rainfall data for these stations were obtained from Korea Meteorological Administration (KMA) and these data were changed to hourly rainfall data. R factor and $I60_{max}$ obtained from hourly rainfall data were compared with R factor and $I30_{max}$ obtained from 10 minute interval data. Linear relation between Average annual R factor obtained from 10 minute interval rainfall and from hourly data was derived with $R^2=0.69$. Correction coefficient was developed for the R factor calculated using hourly rainfall data.. Similarly, the relation was obtained between event wise $I30_{max}$ and $I60_{max}$ with higher $R^2$ value of 0.91. Thus $I30_{max}$ can be estimated from I60max with higher accuracy and thus the hourly rainfall data can be used to determine R factor more precisely by multiplying Energy of each rainfall event with this corrected $I60_{max}$.