• Journal of Korea Water Resources Association
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• v.30 no.1
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• pp.83-93
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• 1997

The purpose of the study is to analyze the sensitivity of the parameters that affect the runoff and water quality in the studied drainage basins. SWMM model is applied to the four drainage basins located at Namgazwa and Sanbon in Seoul and Gray Haven and Kings Creek in the USA. first of all, the optimum values of the parameters which have least simulation error to the observed data, are detected by iteration procedure. These are used as the standard values which are compared against the procedure. These are used as the standard values which are compared against the varied parameter values. In order to catch the effectiveness of the parameters to the computing result, the parameters are changed step by setp, and the results are compared to the standard results in flowerate and quality of the sewer. The study indicates that the discharge is greatly affected by the types of runoff surface, i.e., impervious area remarkably affects the peak flow and runoff volume while the surface storage affects the runoff volume at mild sloped basins. In addition, the major parameters affecting the pollution concentrations and loadings are the contaminant accumulation coefficient per unit area per time and the continuous dry weather days. Furthermore, the factors that affect the water quality during the initial rainfall period are the rainfall intensity, transport capacity coefficient and its power coefficient. Consequently, in order to simulate the runoff-water quality, it is needed to evaluate previous data in the research performed for the studied basins. To accurately estimated from the tributary areas and the rational computation methods of the pollutants calculation should be introduced.

• Atmosphere
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• v.25 no.4
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• pp.623-637
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• 2015

The accurate analysis of water vapor in initial of numerical weather prediction (NWP) model is required as one of the necessary conditions for the improvement of heavy rainfall prediction and reduction of spin-up time on a very-short-range forecast. To study this effect, the impact of a ground-based Global Positioning System (GPS)-Precipitable Water Vapor (PWV) on very-short-range forecast are examined. Data assimilation experiments of GPS-PWV data from 19 sites over the Korean Peninsula were conducted with Advanced Storm-scale Analysis and Prediction System (ASAPS) based on the Korea Meteorological Administration's Korea Local Analysis and Prediction System (KLAPS) included "Hot Start" as very-short-range forecast system. The GPS total water vapor was used as constraint for integrated water vapor in a variational humidity analysis in KLAPS. Two simulations of heavy rainfall events show that the precipitation forecast have improved in terms of ETS score compared to the simulation without GPS-PWV data. In the first case, the ETS for 0.5 mm of rainfall accumulated during 3 hrs over the Seoul-Gyeonggi area shows an improvement of 0.059 for initial forecast time. In other cases, the ETS improved 0.082 for late forecast time. According to a qualitative analysis, the assimilation of GPS-PWV improved on the intensity of precipitation in the strong rain band, and reduced overestimated small amounts of precipitation on the out of rain band. In the case of heavy rainfall during the rainy season in Gyeonggi province, 8 mm accompanied by the typhoon in the case was shown to increase to 15 mm of precipitation in the southern metropolitan area. The GPS-PWV assimilation was extremely beneficial to improving the initial moisture analysis and heavy rainfall forecast within 3 hrs. The GPS-PWV data on variational data assimilation have provided more useful information to improve the predictability of precipitation for very short range forecasts.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.284-291
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• 2010

A simulation modeling for predicting the harvesting date with high potato solids consists of development of mathematical models. The mathematical model on potato growth and its development should be obtained by using agricultural elements which analyze relations of solar radiation quantity, temperature, photon quantity, carbon dioxide exchange rate, water stress and loss, relative humidity, light intensity, and wind etc. But more reliable way to predict harvesting date against climatic change employs in vivo energy consumption for growth and induction shape in a slight environmental adaptation. Therefore, to calculate in vivo energy loss, we take a concept of estimate of the amount of basal metabolism in each tuber on the basis of $Wm={\int}^m_tf(x)dt$ and $Tp=\frac{Tm{\cdot}Wm^{Tp}}{Wm^{Tm}}$. In the validation experiments, results of measuring solid accumulation of potato harvested at simulated date agreed fairly well with the actual measured values in each regional field during the growth period of 2005-2009. The calculation method could be used to predict an appropriate harvesting date for a production of high potato solids according to weather conditions.

• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.257-268
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• 2015

The objective of this study is to assess the dual-polarization radar for flood forecasting. First, radar rainfall has temporal and spatial errors, so estimated radar rainfall was compared with ground observation rainfall to assess accuracy improvement, especially, considering the radar range of observation and increase of the rainfall intensity. The results of this study showed that the error for estimated dual-polarization radar rainfall was less than single-polarization radar rainfall. And in this study, dual-polarization radar rainfall for flood forecasting was assessed using MAP (Mean Areal Precipitation) and SURR (Sejong University Rainfall Runoff) model in Namkang dam watershed. The results of MAP are more accurate using dual-polarization radar. And the results of runoff using dual-polarization radar rainfall showed that peak flow error was reduced approximately 12~63%, runoff volumes error was reduced by approximately 30~42%, and also the root mean square error decreased compared to the result of runoff using single-polarization radar rainfall. The results revealed that dual-polarization radar will contribute to improving the accuracy of the flood forecasting.

• Atmosphere
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• v.29 no.5
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• pp.671-687
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• 2019

This study evaluates the long-term seasonal predictability of summer (June, July and August) heatwaves over South Korea using 30-year (1989~2018) Hindcast data of the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. Heatwave indices such as Number of Heatwave days (HWD), Heatwave Intensity (HWI) and Heatwave Warning (HWW) are used to explore the long-term seasonal predictability of heatwaves. The prediction skills for HWD, HWI, and HWW are evaluated in terms of the Temporal Correlation Coefficient (TCC), Root Mean Square Error (RMSE) and Skill Scores such as Heidke Skill Score (HSS) and Hit Rate (HR). The spatial distributions of daily maximum temperature simulated by WRF are similar overall to those simulated by NCEP-R2 and PNU CGCM. The WRF tends to underestimate the daily maximum temperature than observation because the lateral boundary condition of WRF is PNU CGCM. According to TCC, RMSE and Skill Score, the predictability of daily maximum temperature is higher in the predictions that start from the February and April initial condition. However, the PNU CGCM-WRF chain tends to overestimate HWD, HWI and HWW compared to observations. The TCCs for heatwave indices range from 0.02 to 0.31. The RMSE, HR and HSS values are in the range of 7.73 to 8.73, 0.01 to 0.09 and 0.34 to 0.39, respectively. In general, the prediction skill of the PNU CGCM-WRF chain for heatwave indices is highest in the predictions that start from the February and April initial condition and is lower in the predictions that start from January and March. According to TCC, RMSE and Skill Score, the predictability is more influenced by lead time than by the effects of topography and/or terrain feature because both HSS and HR varies in different leads over the whole region of South Korea.

• Journal of Korean Society of Rural Planning
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• v.26 no.4
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• pp.81-91
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• 2020

This study was conducted to analyse climate change impact on agriculture infrastructure and propose improved measures on vulnerable areas. Recently, Climate change has resulted in damaging effects on agricultural fields through increases in drought intensity and flood risk. It is expected that this impact will increase over time. This study shows that Gyeong-gi and Chung-nam provinces are affected by drought and Gyeong-buk and Gyeong-nam provinces are affected by heavy rain. However, there are also regional variations within each province. Agricultural infrastructure affected by drought may also be affected by heavy rain. Increased damages on the infrastructure due to increased extreme weather events require preventive measures especially in vulnerable areas. In order to minimize the damage by climate change, we need to introduce a reform in the system which selects project region by analysing climate change impacts. Furthermore, impact assessment of climate change from projects such as 'water supply diversification', 'flooded farmland improvement', and 'irrigation facility reinforcement' also need to be adopted to improve the measures. The results of this study are expected to provide a foundation for establishing measures on coping with climate change in the agricultural sector.

• Journal of Korean Society on Water Environment
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• v.32 no.2
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• pp.142-148
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• 2016

The characterization of stormwater runoff from mix land-use catchments with an inadequate sewer network is a challenge. This study focused on characterizing stormwater runoff from the Paldang watershed area based on land-use type and sewer system coverage. A total of 76 sites were monitored during wet weather from seven different counties within Paldang watershed. Public sewer system (PSS) was installed at 48 sites, while 28 sites had no or individual sewer system (ISS) coverage. The results indicated that the sites included in the ISS group with higher forest and paddy land-use percentage exhibit higher values of average event mean concentrations (EMCs) and first flush intensity for suspended solids (SS), total nitrogen (TN), and total phosphorous (TP). In addition, upgrading runoff interception system can capture 59 % of the TP load in the first 43% of runoff within these sites. Similarly, rainfall depth and storm duration showed a positive correlation (R > 0.6) with nutrient loads within ISS group sites, as compared to PSS group. Therefore, these sites are likely to contribute higher TP and TN loads during heavier storm events and should be selected as priority management areas to combat the problem of eutrophication in Paldang reservoir.

• 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 $I60_{max}$.

• Ocean and Polar Research
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• v.43 no.4
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• pp.307-320
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• 2021

Udo Rhodolith Beach is a small-scale, mixed sand-and-gravel beach embayed on the N-S trending rocky coast of Udo, Jeju Island, South Korea. This study analyzes the short-term topographic changes of the beach during the extreme storm conditions of four typhoons from 2016 to 2020: Chaba (2016), Soulik (2018), Lingling (2019), and Maysak (2020). The analysis uses the topographic data of terrestrial LiDAR scanning and drone photogrammetry, aided by weather and oceanographic datasets of wind, wave, current and tide. The analysis suggests two contrasting features of alongshore topographic change depending on the typhoon pathway, although the intensity and duration of the storm conditions differed in each case. During the Soulik and Lingling events, which moved northward following the western sea of the Jeju Island, the northern part of the beach accreted while the southern part eroded. In contrast, the Chaba and Maysak events passed over the eastern sea of Jeju Island. The central part of the beach was then significantly eroded while sediments accumulated mainly at the northern and southern ends of the beach. Based on the wave and current measurements in the nearshore zone and computer simulations of the wave field, it was inferred that the observed topographic change of the beach after the storm events is related to the directions of the wind-driven current and wave propagation in the nearshore zone. The dominant direction of water movement was southeastward and northeastward when the typhoon pathway lay to the east or west of Jeju Island, respectively. As these enhanced waves and currents approached obliquely to the N-S trending coastline, the beach sediments were reworked and transported southward or northward mainly by longshore currents, which likely acts as a major control mechanism regarding alongshore topographic change with respect to Udo Rhodolith Beach. In contrast to the topographic change, the subaerial volume of the beach overall increased after all storms except for Maysak. The volume increase was attributed to the enhanced transport of onshore sediment under the combined effect of storm-induced long periodic waves and a strong residual component of the near-bottom current. In the Maysak event, the raised sea level during the spring tide probably enhanced the backshore erosion by storm waves, eventually causing sediment loss to the inland area.

• Journal of Climate Change Research
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• v.1 no.2
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• pp.109-120
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• 2010

Heat wave is a disaster, which increases morbidity and mortality in temperate regions. Climate model results indicate that both intensity and frequency of heat wave in the future will be increased. This study shows the result about relationship between excess mortality and offensive airmass in 7 metropolitan cities, and an operational Heat-Health Warning System (HHWS) in Korea. Using meteorological observations, the Spatial Synoptic Classification (SSC) has been used to classify each summer day from 1982 to 2007 into specific airmass categories for each city. Through the comparative study analysis of the daily airmass type and the corresponding daily mortality rate, Dry Tropical (DT), and Moist Tropical plus (MT+) were identified as the most offensive airmasses with the highest rates of mortality. Therefore, using the multiple linear regression, forecast algorithm was produced to predict the number of the excess deaths that will occur with each occurrence of the DT and MT+ days. Moreover, each excess death forecast algorithm was implemented for the system warning criteria based on the regional acclimatization differences. HHWS will give warnings to the city's residents under offensive weather situations which can lead to deterioration in public health, under the climate change.