• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.1
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• pp.13-18
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• 2010

In this study the validities of runoff prediction methods are reviewed around ESP (Ensemble Streamflow Prediction) techniques. The improvements of runoff predictions on Yongdam river basin are evaluated by the comparison of different prediction methods including ESP incorporated with qualitative meteorological outlooks provided by meteorological agency as well as the runoff forecasting based on the analysis of the historical rainfall scenarios. As a result it is assessed that runoff predictions with ESP may give rise to more accurate results than the ordinary historical average runoffs. In deed the latter gave the mean of yearly absolute error as to be 60.86 MCM while the errors of the former ones amounted to 44.12 MCM (ESP) and 42.83 MCM (ESP incorporated with qualitative meteorological outlooks) respectively. In addition it is confirmed that ESP incorporated with qualitative meteorological outlooks could improve the accuracy of the results more and more. Especially the degree of improvement of ESP with meteorological outlooks shows rising by 10.8% in flood season and 8% in drought season. Therefore the methods of runoff predictions with ESP can be further used as the basic forecasting information tool for the purpose of the effective watershed management.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.488-488
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• 2015

Intermittent streamflow is common phenomenon in arid and semi-arid regions. To manage water resources of intermittent streamflows, stochactic simulation data is essential; however the seasonally stochastic modeling for intermittent streamflow is a difficult task. In this study, using the periodic Markov chain model, we simulate intermittent monthly streamflow for occurrence and the periodic gamma autoregressive and copula models for amount. The copula models were tested in a previous study for the simulation of yearly streamflow, resulting in successful replication of the key and operational statistics of historical data; however, the copula models have never been tested on a monthly time scale. The intermittent models were applied to the Colorado River system in the present study. A few drawbacks of the PGAR model were identified, such as significant underestimation of minimum values on an aggregated yearly time scale and restrictions of the parameter boundaries. Conversely, the copula models do not present such drawbacks but show feasible reproduction of key and operational statistics. We concluded that the periodic Markov chain based the copula models is a practicable method to simulate intermittent monthly streamflow time series.

• Journal of the Korean Geographical Society
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• v.43 no.6
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• pp.858-872
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• 2008

This study examined the meteorological disaster of Jeju Island in Chosun Dynasty based on historical documents, and analyzed how its government and Jeju Islanders responded to this. Recording cases of abnormal weather days of Jeju Island in Chosun Dynasty were most in 17th Century, and then in 18th Century, 16th Century, 15th Century, and 19th Century in order. For the type of meteorological disaster, storm damage was most serious, and then flood disaster, drought disaster, and snow damage were in order. For the region, Jejumok was mostly damaged from storm and flood, and Daejeonghyeon was mostly from drought. Once meteorological disaster occurred, it was a common thing that it continued with famine. The Chosun government relieved Jeju Islanders by moving the grains of mainland into Jeju Island, and for this, installed Galdujin warehouse, Naripo warehouse, and Jemin warehouse. Also, it tried to resolve chronic famine by moving Jeju people into mainland such as Pyeong'an-do. Corresponding to severe weather, the farmers of Jeju Island implemented agricultural methods such as Dapjeon, Baryeong, molding, and wind-breaking; and the seamen conducted unique arts of navigation such as Hwanjeon, and gravel shipment.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.392-392
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• 2020

최근 기후변화로 인해 가뭄의 규모 및 발생 빈도가 증가하고 있으며, 1994-1995년, 2000-2001년 전국적으로 발생했던 가뭄 상황과 달리 2010년 이후의 가뭄은 지역별로 편중되어 내리는 강수때문에 국소적으로 발생하고 있다. 특히, 2011년부터 2018년까지 연속적으로 국지적인 가뭄이 발생하였고, 2017년에는 경기, 충남, 전남지역을 중심으로 극심한 가뭄이 발생하였다. 우리나라의 경우 강수부족으로 기상, 수문학적 가뭄이 발생한다고 하더라도 농업용 수리시설물에 의한 농업용수 공급이 가능하고, 양수장, 관정 등 농업용수 공급의 형태가 다양하기 때문에 실제로 농업현장에서 체감하는 농업가뭄피해는 시공간적으로 상이하다. 따라서, 강수 부족으로 인한 가뭄사상의 발생에 따른 수문기상학적 특성 및 시공간적인 분포 특성과 농업가뭄피해의 발생 현황, 농업용 저수지의 저수율 변화 및 농업용수 이용과의 관계는 향후 농업가뭄의 지역별 가뭄대책 수립에 중요한 기초자료로 활용할 수 있다. 본 연구에서는 농업가뭄에 대하여 정량적인 가뭄피해를 분석하기 위하여 지역별 가뭄발생면적 및 쌀 생산량과 가뭄사상의 수문기상학적 특성간의 상관성을 분석하고자 한다. 최근 40년간 강수량, 표준강수지수 (Standard Precipitation Index, SPI), 표준강수증발산지수(Standardized Precipitation Evapotranspiration Index, SPEI) 등의 가뭄지표인자와 쌀 생산량, 농업용 저수지 저수율 자료 등 관련 인자들을 수집하여, 농업가뭄발생 및 피해면적과의 정량적인 상관관계를 분석하고자 한다.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.81-92
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• 2019

The objective of this study is to evaluate hydrologic impacts of climate change according to downscaling methods using the Soil and Water Assessment Tool (SWAT) model at watershed scale. We used the APCC Integrated Modeling Solution (AIMS) for assessing various General Circulation Models (GCMs) and downscaling methods. AIMS provides three downscaling methods: 1) BCSA (Bias-Correction & Stochastic Analogue), 2) Simple Quantile Mapping (SQM), 3) SDQDM (Spatial Disaggregation and Quantile Delta Mapping). To assess future hydrologic responses of climate change, we adopted three GCMs: CESM1-BGC for flood, MIROC-ESM for drought, and HadGEM2-AO for Korea Meteorological Administration (KMA) national standard scenario. Combined nine climate change scenarios were assessed by Expert Team on Climate Change Detection and Indices (ETCCDI). SWAT model was established at the Mankyung watershed and the applicability assessment was completed by performing calibration and validation from 2008 to 2017. Historical reproducibility results from BCSA, SQM, SDQDM of three GCMs show different patterns on annual precipitation, maximum temperature, and four selected ETCCDI. BCSA and SQM showed high historical reproducibility compared with the observed data, however SDQDM was underestimated, possibly due to the uncertainty of future climate data. Future hydrologic responses presented greater variability in SQM and relatively less variability in BCSA and SDQDM. This study implies that reasonable selection of GCMs and downscaling methods considering research objective is important and necessary to minimize uncertainty of climate change scenarios.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.311-320
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• 2024

Climate change has been intensifying drought frequency and severity. Such prolonged droughts reduce reservoir levels, thereby exacerbating drought impacts. While previous studies have focused on optimizing reservoir operations using historical data to mitigate these impacts, their scope is limited to analyzing past events, highlighting the need for predictive methods for future droughts. This research introduces a novel approach for predicting minimum inflow at the Seomjingang dam which has experienced significant droughts. This study utilized the Stochastic Analysis Modeling and Simulation (SAMS) 2007 to generate inflow sequences for the same period of observed inflow. Then we simulate reservoir operations to assess firm yield and predict minimum inflow through synthetic inflow analysis. Minimum inflow is defined as the inflow where firm yield is less than 95% of the synthetic inflow in many sequences during periods matching observed inflow. The results for each case indicated the firm yield for the minimum inflow is on average 9.44 m³/s, approximately 1.07 m³/s lower than the observed inflow's firm yield of 10.51 m³/s. The minimum inflow estimation can inform reservoir operation standards, facilitate multi-reservoir system reviews, and assess supplementary capabilities. Estimating minimum inflow emerges as an effective strategy for enhancing water supply reliability and mitigating shortages.

• Journal of Climate Change Research
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• v.6 no.1
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• pp.55-60
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• 2015

Agro-Meteorological Information Service (AMIS) network has been established since 2001 by Rural Development Administration (RDA) in Korea, and has provided access to current and historical weather data with useful information for agricultural activities. AMIS network includes 158 automated weather stations located mostly in farm region, with planning to increase by 200 stations until 2017. Agrometeorological information is disseminated via the web site (http://weather.rda.go.kr) to growers, researchers, and extension service officials. Our services will give enhanced information from observation data (temperature, precipitation, etc.) to application information, such as drought index, agro-climatic map, and early warning service. AMIS network of RDA will help the implementation of an early warning service for weather risk management.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.999-1009
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• 2022

The Chuncheon Mullori area is an underprivileged area for water welfare that does not have a local water supply system. Here, water is supplied to the village by using a small-scale water supply facility that uses underground water and underground water as the source. To solve the problem of water shortage during drought and to prepare for the increasing water demand, a sand dam was installed near the valley river, and this facility has been operating since May 2022. In this study, in order to evaluate the reliability of water supply when a sand dam is assumed during a drought in the past, groundwater runoff simulation results using MODFLOW were used to generate inflow data from 2011 to 2020, an unmeasured period. After performing SWAT-K basin hydrologic modeling for the watershed upstream of the existing water intake source and the sand dam, the groundwater runoff was calculated, and the relative ratio of the monthly groundwater runoff for the previous 10 years to the monthly groundwater runoff in 2021 was obtained. By applying this ratio to the 2021 inflow time series data, historical inflow data from 2011 to 2020 were generated. As a result of analyzing the availability of water supply during extreme drought in the past for three cases of demand 20 m³/day, 50 m³/day, and 100 m³/day, it can be confirmed that the reliability of water supply increases with the installation of sand dams. In the case of 100 m³/day, it was analyzed that the reliability exceeded 90% only when the existing water intake source and the sand dam were operated in conjunction. All three operating conditions were evaluated to satisfy 50 m³/day or more of demand based on 95% reliability of water supply and 30 m³/day or more of demand based on 99% of reliability.

• Journal of Life Science
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• v.27 no.2
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• pp.194-201
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• 2017

Rapeseed (Brassica napus L.) is an oil crop classified as Brassicaceae, and it is widely grown worldwide. To develop a drought-resistant rapeseed, the ${\beta}$-glucosidase 1 (AtBG1) gene was introduced into rapeseed because drought- and salt-resistance phenotypes were observed when the AtBG1 gene was overexpressed in arabidopsis. Newly developed genetically modified crop must be proved to be safe. Safety assessments are based on the historical usage and scientific reports of a crop. In this study, we examined the potential acute oral toxicity of AtBG1 protein expressed in genetically modified (GM) rapeseed and calculated the minimum lethal dose at 6 weeks in both male and female ICR mice. AtBG1 protein was fed at a dose of 2,000 mg/kg body weight in five male and five female mice according to the marginal capacity concentration of OECD, 2,000 mg/15 ml/kg. Mortalities, clinical findings, and body weight changes were monitored for 14 days after dosing, and postmortem necropsy was performed on day 14. This study showed that no deaths occurred in the test group, and AtBG1 protein did not result in variations in common symptoms, body weight, and postmortem findings between the two groups. This showed that the minimum lethal dose of AtBG1 protein expressed in transgenic rapeseed exceed 2,000 mg/kg body weight in both sexes.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.515-529
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• 2022

Identifying the available water resources amount is an essential process in establishing a sustainable water resources management plan. Dam facility is a major infrastructure storing and supplying water during the dry season, and the water supply yield of the dam varies depending on dam inflow conditions or operation rule. In South Korea, water supply yield of dam is calculated by reservoir simulation based on observed historical dam inflow data. However, the water supply capacity of a dam can be underestimated or overestimated depending on the existence of historical drought events during the simulation period. In this study, probabilistic inflow data was generated and used to estimate the appropriate range of the water supply yield of hydropower dams. That is, a method for estimating the probabilistic dam inflow that fluctuates according to climatic and socio-economic conditions and the range of water supply yield for hydropower dams was presented, and applied to hydropower dams located in the Han river in South Korea. It is expected that the understanding water supply yield of the hydropower dams will become more important to respond to climate change in the future, and this study will contribute to national water resources management planning by providing potential range of water supply yield of hydropower dams.