• Water for future
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• v.7 no.1
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• pp.65-70
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• 1974

According to the simplified Gringorten's method of extreme values from data samples, daily maximum precipitation and return period in Seoul was estimated. And also, it was known that the distribution of daily maximum precipitation of Seoul area belong th an exponential type of distribution.

• Journal of Environmental Science International
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• v.19 no.9
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• pp.1109-1118
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• 2010

Characteristics of precipitation and temperature in Ulleung-do and Dok-do were analyzed with hourly accumulated precipitation and mean temperature data obtained from Automatic Weather System(AWS) for latest four years(2005~2008). In Ulleung-do, total annual mean precipitation for this period is 1,574.4 mm, which shows larger amount than 1434.2 mm of whole Korean peninsula for latest 10 years(1999~2008) and 1,236.2 mm at Ulleung-do on common years(1971~2000), shows that the trend of precipitation gradually increases during the recent years. This amount is also 1.4 times larger than the total annual mean precipitation of 660.1 mm in Dok-do. Mean precipitation intensity(mm $h^{-1}$) at each time of a day in each month at Ulleung-do represents that the maximum values larger than $3.0\;mm\;h^{-1}$ were shown in May and on 0200 LST, whereas these were found in August and 0700 LST with $3.1\;mm\;h^{-1}$ in Dok-do. The difference of the precipitation amount and its intensity between Uleung-do and Dok-do is explained by the topological effect came from each covering area, and this fact is also identified from similar comparison of the precipitation characteristics for the islands in West Sea. The annual mean temperature of $14.0^{\circ}C$ in Dok-do is $1.2^{\circ}C$ higher than that of $12.8^{\circ}C$ in Ulleung-do. Trends of monthly mean temperature in both islands are shown to increase for the observed period.

• Journal of the Korean earth science society
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• v.37 no.1
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• pp.29-39
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• 2016

In this study, we estimated solar radiation by multiple regression analysis using sunshine duration and precipitation data, which are highly correlated to solar radiation. We found the regression equation using data obtained from GROM (Gangwon Regional Office of Metrology, station 105, 1980-2007) located in Gangneung, South Korea and validated the equation by applying data obtained from new GROM (newly relocated, station 104, 2009-2014) and data obtained from GWNU (Gangneung-Wonju National University, 2013-2014) located between stations 104 and 105. By using sunshine duration data alone, the estimation using data from station 104 resulted in a correlation coefficient of 0.96 and a standard error of $1.16MJm^{-2}$, which was similar to the previous results; the estimation using data from GWNU yielded better results with a correlation coefficient of 0.99 and a standard error of $0.57MJm^{-2}$. By using sunshine duration and precipitation data, the estimation (using data from station 104) yielded a correlation coefficient of 0.96 and a standard error of $0.99MJm^{-2}$, resulting in a lower standard error compared to what was obtained using sunshine duration data alone. The maximum solar radiation bias increased from -26.6% (March 2013) to -31.0% (February 2011) when both sunshine duration and precipitation data were incorporated into the estimation rather than when sunshine duration data alone was incorporated. This was attributed to the concentrated precipitation found during May and July-September, which resulted in negative coefficients of the estimating equation in other months. Therefore, the monthly average solar radiation should be estimated carefully when employing the monthly average precipitation for those places where precipitation is concentrated during summer, such as the Korean peninsula.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.83-94
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• 2010

The objective of this study was to determine the best probability distributions of annual, seasonal and monthly precipitation in Korea. Data observed at 32 stations in Korea were analyzed using the L-moment ratio diagram and the average weighted distance (AWD) to identify the best probability distributions of each precipitation. The probability distribution was best represented by 3-parameter Weibull distribution (W3) for the annual precipitation, 3-parameter lognormal distribution (LN3) for spring and autumn seasons, and generalized extreme value distribution (GEV) for summer and winter seasons. The best probability distribution models for monthly precipitation were LN3 for January, W3 for February and July, 2-parameter Weibull distribution (W2) for March, generalized Pareto distribution (GPA) for April, September, October and November, GEV for May and June, and log-Pearson type III (LP3) for August and December. However, from the goodness-of-fit test for the best probability distributions of the best fit, GPA for April, September, October and November, and LN3 for January showed considerably high reject rates due to computational errors in estimation of the probability distribution parameters and relatively higher AWD values. Meanwhile, analyses using data from 55 stations including additional 23 stations indicated insignificant differences to those using original data. Further studies using more long-term data are needed to identify more optimal probability distributions for each precipitation.

• Journal of Korea Water Resources Association
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• v.47 no.11
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• pp.1095-1105
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• 2014

A spatial downscaling method using the Support Vector Machine (SVM) Regression for 25 km Tropical Rainfall Measuring Mission (TRMM) Monthly precipitation is proposed. The nonlinear relationship among hydrometeorological variables and precipitation was effectively depicted by the SVM for predicting downscaled grid precipitation. The accuracy of spatially downscaled precipitation was estimated by comparing with rain gauge data from sixty-four stations and found to be improved than the original TRMM data in overall. Especially the positive bias of the original TRMM data was effectively removed after the downscaling procedure. The spatial distributions of 25 km and 1 km grid precipitation were generally similar, while the local spatial trend was better detected by 1 km grid precipitation. The downscaled grid data derived from the proposed method can be applied in hydrological modelling for higher accuracy and further be studied for developing optimized downscaling method incorporation other regression methods.

• Journal of Climate Change Research
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• v.2 no.2
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• pp.133-141
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• 2011

This study is to identify the trend of climate change in Gangwon-do by examining accumulated climate data such as temperature and precipitation in Gangneung city over the past about 100 years. The annual mean temperature and precipitation in Gangneung have increased by $1.4^{\circ}C$ and 14.7%, respectively, over the last 98 years (1912~2009). The trends of Gangneung showed that precipitation has intensified as the number of precipitation days decreased while its amount increased during the period. Based on the temperature data, spring and summer began earlier whereas the onsets of fall and winter were delayed. Summer has become longer and winter shorter by about a month. Averaging observation data from seven weather stations in Gangwon-do, the annual mean temperature and precipitation have increased by $0.8^{\circ}C$ and 21.0% respectively over the last 37 years (1973~2009). By region, Wonju city recorded the biggest increase of $1.6^{\circ}C$ in the annual mean temperature while Sokcho city the smallest increase of $0.4^{\circ}C$. In the annual mean precipitation, Daegwallweong recorded the biggest change of 22.2% and Wonju city the smallest of 12.0%.

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.669-676
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• 2006

Hydrological factors, especially the spatial distribution of interpretation on precipitation is often topic of interest in studying of water resource. The popular methods such as Thiessen method, inverse distance method, and isohyetal method are limited in calculating the spatial continuity and geographical characteristics. This study was intended to overcome those limitations with improved method that will yield higher accuracy. The monthly and yearly precipitation data were produced and compared with the observed daily precipitation to find correlation between them. They were then used as secondary variables in Co-kriging method, and the result was compared with the outcome of existing methods like inverse distance method and kriging method. The comparison of the data showed that the daily precipitation had high correlation with corresponding year's average monthly amounts of precipitation and the observed average monthly amounts of precipitation. Then the result from the application of these data for a Co-kriging method confirmed increased accuracy in the modeling of spatial distribution of precipitation, thus indirectly reducing inconsistency of the spatial distribution of hydrological factors other than precipitation.

• Korean Journal of Soil Science and Fertilizer
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• v.35 no.2
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• pp.87-92
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• 2002

Soil erosion is detrimental to sustain soil productivity in north Korea, since agriculture of this country depends largely upon the slope land in mountainous area. Taking any measure for protection from erosion should be based on prediction of soil loss. Estimation of rainfall factor, R, in north Korea for the Universal Soil Loss Equation was attempted. The monthly precipitation data of the twenty six locations provided by the Korean Meteorological Adminstration were used. From the relationship between II_30 and the July-August precipitation concentration percents, the regional adjustment factor was obtained. The rainfall factor was calculated with the monthly precipitation data and the regional adjustment factor. The annual precipitation in north Korea ranged from 606 to 1,520mm, and the July-August precipitation concentration percents were 34.4 to 53.8. The regional adjustment factor ranged from 0.53 to 1.33 showing lower value in the highland and east coastal region than in the mid mountainous inland and west region. The R-factor value estimated from the monthly precipitation and the regional adjustment factor ranged from 107 to 483, which was lower than average value in south Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.273-277
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• 2010

This research was performed to examine changes in the timing of the growth of crops along with changes in temperatures due tochanges and to analyze the change of water-supply-reliability by adding an analysis of the change of agricultural water supply patterns in the basin area of Miryang dam in Korea. Had-CM3 model from U.K. was the tool adopted for the GCM model, a stochastic, daily-meteorology-generation-model called LARS-WG was alsoused for downscaling and for the climate change scenario (A1B) which represents Korea's circumstances best. First of all, to calculate changes in the timing of the growth of crops during this period, the theory of GDD was applied. Except for the period of transplanting and irrigation, there was no choice but to find the proper accumulated temperature by comparing actual temperature data and the supply pattern of agricultural use due to limited temperature data. As a result, proper temperatures were found for each period. $400^{\circ}C$ for the preparation period of a nursery bed, $704^{\circ}C$ for a nursery bed's period, $1,295^{\circ}C$ for the rice-transplanting period, $1,744^{\circ}C$ for starting irrigation, and $3,972^{\circ}C$ for finishing irrigation. To analyze future agricultural supply patter changes, the A1B scenario of Had-CM3 model was adopted, and then Downscaling was conducted adopting LARS-WG. To conduct a stochastical analysis of LARS-WG, climate scenarios were generated for the periods 2011~2030, 2046~2065, 2080~2099 using the data of precipitation andMax/Min temperatures collected from the Miryang gauging station. Upon reviewing the result of the analysis of accumulated temperatures from 2011~2030, the supply of agricultural water was 10 days earlier, and in the next periods-2046~2065, 2080~2099 it also was 10 days earlier. With these results, it is assumed that the supply of agricultural water should be about 1 month ahead of the existing schedule to meet the proper growth conditions of crops. From the results of the agricultural water supply patterns should be altered, but the reliability of water supply becomes more favorable, which is caused from the high precipitation change. Furthermore, since the unique characteristics of precipitation in Korea, which has high precipitation in the summer, water-supply-reliability has a pattern that the precipitation in September could significantly affect the chances of drought the following winter and spring. It could be more risky to make changes to the constant supply pattern under these conditions due to the high uncertainty of future precipitation. Although, several researches have been conducted concerning climate changes, in the field of water-industry, those researches have been solely dependent on precipitation. Even so, with the high uncertainty of precipitation, it is difficult for it to be reflected in government policy. Therefore, research in the field of water-supply-patterns or evapotranspiration according to the temperature or other diverse effects, which has higher reliability on anticipation, could obtain more reliable results in the future and that could result in water-resource maintenance to be safer and a more advantageous environment.

• Water for future
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• v.27 no.3
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• pp.71-82
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• 1994

A statistical characteristics, relations of calendar and water year, and frequencies of precipitaion which are necessary for water resources planning were analyzed with long historical data(1905-1991 years). And the analysis of precipitation of the drought periods in 1967-1968 years was carried out. The study basins are the five major rivers in Korea. As a results of this study, annual precipitation shows an increasing trend but its variation has no statistical significance. The rellations of calendar and water year precipitation is presented, it shows that there are little difference of the total precipitation between them. The annual minimum series of total precipitation for the periods of 3, 6, 9, and 12 months by water year are constructed, and frequency precipitation for each periods using 2-parameter lognormal distribution is presented. The analysis of the precipitation in 1967-1968 years shows in a natural river basins that it would be a moderate drought, if dry seasons(Oct-May) or wet seasons(Jun-Sep) has 75 percents of historical mean precipitation of the same periods. And if it has less than 60 percents of historical mean precipitation, it would be a severe drought.