• Atmosphere
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• v.29 no.4
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• pp.451-461
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• 2019

Medium-range forecast is highly dependent on ensemble forecast data. However, operational weather forecasters have not enough time to digest all of detailed features revealed in ensemble forecast data. To utilize the ensemble data effectively in medium-range forecasting, representative weather patterns in East Asia in this study are defined. The k-means clustering analysis is applied for the objectivity of weather patterns. Input data used daily Mean Sea Level Pressure (MSLP) anomaly of the ECMWF ReAnalysis-Interim (ERA-Interim) during 1981~2010 (30 years) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Using the Explained Variance (EV), the optimal study area is defined by 20~60°N, 100~150°E. The number of clusters defined by Explained Cluster Variance (ECV) is thirty (k = 30). 30 representative weather patterns with their frequencies are summarized. Weather pattern #1 occurred all seasons, but it was about 56% in summer (June~September). The relatively rare occurrence of weather pattern (#30) occurred mainly in winter. Additionally, we investigate the relationship between weather patterns and extreme weather events such as heat wave, cold wave, and heavy rainfall as well as snowfall. The weather patterns associated with heavy rainfall exceeding 110 mm day^-1 were #1, #4, and #9 with days (%) of more than 10%. Heavy snowfall events exceeding 24 cm day^-1 mainly occurred in weather pattern #28 (4%) and #29 (6%). High and low temperature events (> 34℃ and < -14℃) were associated with weather pattern #1~4 (14~18%) and #28~29 (27~29%), respectively. These results suggest that the classification of various weather patterns will be used as a reference for grouping all ensemble forecast data, which will be useful for the scenario-based medium-range ensemble forecast in the future.

• Journal of Environmental Science International
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• v.22 no.2
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• pp.235-242
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• 2013

The purpose of this article is analyzing the impacts of climate change on winter chinese cabbage yield in Korea, with employing a panel data regression model. Our results show that there is a negative impacts of high temperature and precipitation amount on winter chinese cabbage yields. Especially high temperature and rainfall in September cause serious damage to winter chinese cabbage yield. According to the reduction schedule on greenhouse gas emission(RCP 4.5 scenario.), winter chinese cabbage yield would be 7.7% lower than it is, for reasons of high temperature and rainfall damages by the end of 21st century.

• The Korean Journal of Quaternary Research
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• v.19 no.1
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• pp.41-46
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• 2005

This study discusses the soil erosion on hillslopes and sediment deposition in lakes within catchments in South Korea. In order to determine seasonal variations of sedimentation in Yeongcheon and Seondong lakes, the sediment traps were set in the deep part of both lakes and lake sediments have been sampledmonthly from July 2004 to August 2005. Some properties such as highmineral content, fine particle size and high particle density in the Yeongcheon Lake indicate intensive soil erosion, sediment transportation and deposition throughout the catchment for a long time. The high sediment yield in the Seondong Lake is related with higher weathering intensity and extreme soil erosion by running water due to higher seasonal rainfall amount. Rates of erosion and sedimentation in the Seondong Lake are estimated to be higher than those of the Yeongcheon Lake, suggesting that the Seondong Lake is associated with higher precipitation, smaller catchment area, and extreme soil vulnerability to ephemeral erosion by overland flow during the heavy rainfall event. Consequently, both catchments are characterized by different erosion and sedimentation processes, as well as different geomorphic factors (bedrock, soil structure, rainfall intensity and catchment area).

• Journal of Environmental Science International
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• v.22 no.5
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• pp.555-562
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• 2013

Jeju Island, the heaviest raining area in Korea, is a volcanic Island located at the southernmost of Korea, but most streams are of the dry due to its hydrological/geological characteristics different from those of inland areas. Therefore, there are limitations in applying the results from the mainland to the studies on stream run-off characteristics analysis and water resource analysis of Jeju Island. In this study, the SWAT(soil & water assessment tool) model is used for the Hwabuk stream watershed located east of the downtown to calculate the long-term stream run-off rate, and WMS(watershed modeling system) and HEC-HMS(hydrologic modeling system) models are used to figure out the stream run-off characteristics due to short-term heavy rainfall. As the result of SWAT modelling for the long-term rainfall-runoff model for Hwabuk stream watershed in 2008, 5.66% of the average precipitation of the entire basin was run off, with 3.47% in 2009, 8.12% in 2010, and root mean square error(RMSE) and determination coefficient($R^2$) was 496.9 and 0.87, respectively, with model efficient(ME) of 0.72. From the results of WMS and HEC-HMS models which are short-term rainfall-runoff models, unless there was a preceding rainfall, the runoff occurred only for rainfall of 40mm or greater, and the run-off duration averaged 10~14 hours.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.105-116
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• 2011

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, the exact relationship and the spatial variability analysis of hydrometeorological elements and characteristic factors is critical elements to reduce the uncertainty in rainfall -runoff model. In this study, radar rainfall grid resolution and grid resolution depending on the topographic factor in rainfall - runoff models were how to respond. In this study, semi-distribution of rainfall-runoff model using the model ModClark of Inje, Gangwon Naerin watershed was used as Gwangdeok RADAR data. The completed ModClark model was calibrated for use DEM of cell size of 30m, 150m, 250m, 350m was chosen for the application, and runoff simulated by the RADAR rainfall data of 500m, 1km, 2km, 5km, 10km from 14 to 17 on July, 2006. According to the resolution of each grid, in order to compare simulation results, the runoff hydrograph has been made and the runoff has also been simulated. As a result, it was highly runoff simulation if the cell size is DEM 30m~150m, RADAR rainfall 500m~2km for peak flow and runoff volume. In the statistical analysis results, if every DEM cell size are 500m and if RADAR rainfall cell size is 30m, relevance of model was higher. Result of sensitivity assessment, high index DEM give effect to result of distributed model. Recently, rainfall -runoff analysis is used lumped model to distributed model. So, this study is expected to make use of the efficiently decision criteria for configurated models.

• Journal of Soil and Groundwater Environment
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• v.18 no.1
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• pp.85-93
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• 2013

This study is conducted to evaluate the leaching of contaminants from mine tailing by natural water and finally to estimate the leaching and transportation of heavy metal contaminants by rainfall. In order to identify contaminated heavy metal of soil, 17 soil, 2 tailing and 2 waste dump and 2 control samples were taken at mine area and analyzed total metal contents. The leaching experiments were conducted using distilled water. Cu, Pb, Zn was extracted from the reddish mine tailing in a short period time, especially the extraction rate of Cu (45.0%) was highest. The contaminants were leached from the yellowish mine tailing within an hour and the leaching rate of Cd (42.0%) and Zn (17.2%) were relatively high. The reddish soil from the waste dump showed leaching of Cu (5.1%), Pb (4.0%) and Zn (3.3%), however the leaching rate was low except Mi (14.2%). From the yellowish soil sampled from the dumping site, the leaching of Cu (8.2%) and Ni (9.7%) was high while the leaching of Zn (0.2%) were relatively low.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.706-714
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• 2012

The Korea Meteorological Administration provided the recent four-years records of weather dataset for our very short-term heavy rainfall prediction. We divided the dataset into three parts: train, validation and test set. Through feature selection, we select only important features among 72 features to avoid significant increase of solution space that arises when growing exponentially with the dimensionality. We used a differential evolution algorithm and two classifiers as the fitness function of evolutionary computation to select more accurate feature subset. One of the classifiers is Support Vector Machine (SVM) that shows high performance, and the other is k-Nearest Neighbor (k-NN) that is fast in general. The test results of SVM were more prominent than those of k-NN in our experiments. Also we processed the weather data using undersampling and normalization techniques. The test results of our differential evolution algorithm performed about five times better than those using all features and about 1.36 times better than those using a genetic algorithm, which is the best known. Running times when using a genetic algorithm were about twenty times longer than those when using a differential evolution algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3B
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• pp.355-361
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• 2008

A water quality analysis of rainwater collected from catchment equipment ($2m{\times}1m$) was conducted to determine its suitability for domestic purposes, in this study. As the results of analysis, the pH of rainwater was $6.3{\pm}0.3$, and the turbidity of rainwater was over the 5 times than drinking water guidelines. For the usage of rainwater as the domestic and drinking water, the rainwater is need to treat. The analysis values of heavy metal as the Pb, Cd, Fe, Mn, ${Cr_6}^+$ and Cu was satisfied with drinking guidelines. Rainwater quality was improved in the rainfall duration. Overall results of analysis support the possibility of rainwater as the domestic and drinking water.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.791-803
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• 2016

Recently, frequency of extreme rainfall events in South Korea has been substantially increased due to the enhanced climate variability. Korea is prone to flooding due to being surrounded by mountains, along with high rainfall intensity during a short period. In the past three decades, an increase in the frequency of heavy rainfall events has been observed due to enhanced climate variability and climate change. This study aimed to analyze extreme rainfalls informed by their frequency of occurrences using a long-term rainfall data. In this respect, we developed a Poisson-Generalized Pareto Distribution (Poisson-GPD) based rainfall frequency method which allows us to simultaneously explore changes in the amount and exceedance probability of the extreme rainfall events defined by different thresholds. Additionally, this study utilized a Bayesian approach to better estimate both parameters and their uncertainties. We also investigated the synoptic patterns associated with the extreme events considered in this study. The results showed that the Poisson-GPD based design rainfalls were rather larger than those of based on the Gumbel distribution. It seems that the Poisson-GPD model offers a more reasonable explanation in the context of flood safety issue, by explicitly considering the changes in the frequency. Also, this study confirmed that low and high pressure system in the East China Sea and the central North Pacific, respectively, plays crucial roles in the development of the extreme rainfall in South Korea.

• Journal of Korea Water Resources Association
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• v.46 no.2
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• pp.123-137
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• 2013

This study investigated impacts of the two different types of El Ni$\tilde{n}$o on summer rainfall (June-September) in the Han River and its sub-basins. The patterns of rainfall anomalies show a remarkable difference between conventional El Ni$\tilde{n}$o and El Ni$\tilde{n}$o Modoki years. During conventional El Ni$\tilde{n}$o years, it was found that the Han River basins show decreases in the seasonal rainfall totals with high variations (CV=0.4). In contrast, during El Ni$\tilde{n}$o Modoki years, distinct positive anomalies appear in the Han River basin with a relatively small variation (CV=0.23). In addition, 11 out of 30 sub-basins show significant above-normal rainfall in southern part of the Han River Basin. For El Ni$\tilde{n}$o Modoki years, the number of heavy rainy days exceeding 30 mm/day and 50 mm/day were 9.9-day and 5.4-day, respectively. Consequently, this diagnostic study confirmed that El Ni$\tilde{n}$o Modoki has significant impacts on the variability of summer rainfall over the Han River Basin. We expect the results presented here provide useful information for the stability of the regional water supply system, especially for basins like the Han River Basin showing relatively high variability in seasonal rainfall.