• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.43-54
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• 2023

Due to climate change, drought and flood occurrences have been increasing. Accurate projections of watershed discharges are imperative to effectively manage natural disasters caused by climate change. However, climate change and hydrological model uncertainty can lead to imprecise analysis. To address this issues, we used two lumped models, IHACRES and GR4J, to compare and analyze the changes in discharges under climate stress scenarios. The Hapcheon and Seomjingang dam basins were the study site, and the Nash-Sutcliffe efficiency (NSE) and the Kling-Gupta efficiency (KGE) were used for parameter optimizations. Twenty years of discharge, precipitation, and temperature (1995-2014) data were used and divided into training and testing data sets with a 70/30 split. The accuracies of the modeled results were relatively high during the training and testing periods (NSE>0.74, KGE>0.75), indicating that both models could reproduce the previously observed discharges. To explore the impacts of climate change on modeled discharges, we developed climate stress scenarios by changing precipitation from -50 % to +50 % by 1 % and temperature from 0 ℃ to 8 ℃ by 0.1 ℃ based on two decades of weather data, which resulted in 8,181 climate stress scenarios. We analyzed the yearly maximum, abundant, and ordinary discharges projected by the two lumped models. We found that the trends of the maximum and abundant discharges modeled by IHACRES and GR4J became pronounced as changes in precipitation and temperature increased. The opposite was true for the case of ordinary water levels. Our study demonstrated that the quantitative evaluations of the model uncertainty were important to reduce the impacts of climate change on water resources.

• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.25-35
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• 2014

The objective of this study is to evaluate TOPLATS land surface model performance through comparison of results of water and energy balance analysis. The study area is selected Nakdong river basin and high resolution hydrometeorological components of which spatio-temporal resolution is 1 hr and 1 km are simulated during 2003 to 2013. The simulated daily and monthly depth of flows are well fitted with the observed one on Andong and Hapcheon dam basin. In results of diurnally analysis of energy components, change pattern throughout the day of net radiation, latent heat, sensible heat, and ground heat under energy balance analysis have higher accuracy than ones under water balance analysis at C3 and C4 sites. Especially, root mean square errors of net radiation and latent heat at C4 site are shown very low as 22.18 $W/m^2$ and 7.27 $W/m^2$, respectively. Mean soil moisture and evapotranspiration in summer and winter are simulated as 36.80%, 33.08% and 222.40 mm, 59.95 mm, respectively. From this result, when we need high resolution hydrometeorological components, energy balance analysis is more reasonable than water balance analysis. And this results will be used for monitor and forecast of weather disaster like flood and draught using spatial hydrometeorological information.

• Journal of Korean Society of Disaster and Security
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• v.14 no.3
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• pp.17-27
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• 2021

In this study, classification models were built using machine learning techniques that can classify the soil creep risk into three classes from A to C (A: risk, B: moderate, C: good). A total of six machine learning techniques were used: K-Nearest Neighbor, Support Vector Machine, Logistic Regression, Decision Tree, Random Forest, and Extreme Gradient Boosting and then their classification accuracy was analyzed using the nationwide soil creep field survey data in 2019 and 2020. As a result of classification accuracy analysis, all six methods showed excellent accuracy of 0.9 or more. The methods where numerical data were applied for data training showed better performance than the methods based on character data of field survey evaluation table. Moreover, the methods learned with the data group (R1~R4) reflecting the expert opinion had higher accuracy than the field survey evaluation score data group (C1~C4). The machine learning can be used as a tool for prediction of soil creep if high-quality data are continuously secured and updated in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.1
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• pp.38-47
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• 2002

This paper demonstrates a regional analysis of landslide occurrence potential by applying geographic information system to the Kumi City selected as a pilot study area. The estimate criteria related to natural and humane environmental factors which affect landslides were first established. A slope map and a aspect map were extracted from DEM, which was generated from the contour layers of digital topographic maps, and a NDVI vegetation map and a land cover map were obtained through satellite image processing. After the spatial database was constructed, indexes of landslide occurrence potential were computed and then a few landslide-potential areas were extracted by an overlay method. It was ascertained that there are high landslide-potential at areas of about 30% incline, aspects including either south or east at least, adjacent to water areas or pointed end of the water system, in or near fault zones, covered with medium vegetable. For more synthetic and accurate analysis, soil data, forest data, underground water level data, meteorological data and so on should be added to the spatial database.

• Journal of Wetlands Research
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• v.19 no.3
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• pp.345-352
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• 2017

The average global temperature on Earth has increased by about $0.85^{\circ}C$ since 1880 due to the global warming. The temperature increase affects hydrologic phenomenon and so the world has been suffered from natural disasters such as floods and droughts. Therefore, especially, in the aspect of water deficit, we may require the accurate prediction of water demand considering the uncertainty of climate in order to establish water resources planning and to ensure safe water supply for the future. To do this, the study evaluated future water balance and water deficit under the climate change for Anseong river basin in Korea. The future rainfall was simulated using RCP 8.5 climate change scenario and the runoff was estimated through the SLURP model which is a semi-distributed rainfall-runoff model for the basin. Scenario and network for the water balance analysis in sub-basins of Anseong river basin were established through K-WEAP model. And the water demand for the future was estimated by the linear regression equation using amounts of water uses(domestic water use, industrial water use, and agricultural water use) calculated by historical data (1965 to 2011). As the result of water balance analysis, we confirmed that the domestic and industrial water uses will be increased in the future because of population growth, rapid urbanization, and climate change due to global warming. However, the agricultural water use will be gradually decreased. Totally, we had shown that the water deficit problem will be critical in the future in Anseong river basin. Therefore, as the case study, we suggested two alternatives of pumping station construction and restriction of water use for solving the water deficit problem in the basin.

• Journal of the Korean earth science society
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• v.34 no.6
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• pp.492-506
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• 2013

The historical accounts and materials about the eruption of Mt. Baekdusan as observed by the geological survey is now showing some signs of waking from a long slumber. As a response of the volcanic eruption of Mt. Baekdusan, water release may occur from the stored water in Lake Cheonjii caldera. The volcanic flood is crucial in that it has huge potential energy that can destruct all kinds of man-made structures and that its velocity can reach up to 100 km $hr^{-1}$ to cover hundreds of kilometers of downstream of Lake Cheonji. The ultimate goal of the study is to estimate the level of damage caused by the volcanic flood of Lake Cheon-Ji caldera. As a preliminary study a scenario-based numerical analysis is performed to build hydrographs as a function of time. The analysis is performed for each scenario (breach, magma uplift, combination of uplift and breach, formation of precipitation etc.) and the parameters to require a model structure is chosen on the basis of the historic records of other volcanos. This study only considers the amount of water at the rim site as a function of time for the estimation whereas the downstream routing process is not considered in this study.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1032-1035
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• 2008

제주도 연악해역의 해일재해의 현황을 파악하기 위하여 제주도 연안해역의 폭풍해일과 기상조에 등에 의한 해일발생 및 피해의 자료를 분석 검토하고 제주도 연안해일의 위험도를 분석하기 위하여 제주도 연안해역을 대상으로 과거 태풍 중 각종 기록경신과 많은 피해규모를 준 태풍들을 대상으로 바람장 및 해일고를 분석 검토하여 태풍의 진로에 따른 해수면 상승을 산정하기위해 폭풍해일 수치모형(POM) 실험을 실시하여 폭풍해일고를 산정하였다. 제주항과 서귀포항 주변해역의 폭풍해일고를 산출하기 위해 16년간($1987{\sim}2003$)까지의 우리나라에 영향을 미친 태풍 중 8개를 선정(Maemi, Rusa, Prapiroon, Olga, Yanni, Janis, Gladys, Thelma)하여 폭풍해일고를 산출하였다. 수치모의 한 결과를 보면, 제주와 서귀포 연안해역에서 발생한 8개의 태풍에 대한 폭풍해일고의 발생시각은 대체적으로 관측된 해일고의 발생시각 보다 약간 늦게 해일이 발생하였지만 전체적인 해일의 시간변화나 크기는 비교적 잘 재현된 것으로 나타났다. 제주항 연안해역의 서귀포항 연안해역보다 높은 해일고를 보였으며, 해일고는 제주항, 서귀포항 모두 1m를 넘지 않았다. 제주항이 서귀포항에 비해 약간 높게 나온 이유는 태풍의 위치, 지형 및 수심, 태풍이 통과할 당시의 조석상황 등의 차이인 것으로 사료된다. 또한, 제주항과 서귀포항 연안해역이 폭풍해일고가 서해안이나 남해안에 비해 작게 나타났는데, 이는 제주도 해안선이 비교적 평탄하고 평행하게 이루어 졌으며 남해안에 비해 수심이 깊고 만의 형태나 V자형 및 긴내만이 발달한 지형이 없기 때문인 것으로 사료된다. 보다 정밀한 예측을 위해서는 정밀한 수심자료 및 격자를 이용한 계산의 결과가 필요하며, 연안개발로 인한 지형과 수심변화에 따른 지속적인 수치해도 DB구축이 요구된다.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.99-109
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• 2009

In this study, often the spatial distribution of precipitation was analyzed using the quantile with regional frequency analysis and spatial analysis to find out the detail distribution of extreme precipitation for preventing the disaster in the region of Gangwon. The hourly precipitation data of 66 stations in Gangwon were used. As the results of regional frequency analysis, it shows that the generalized logistic (GLO) distribution is the best for the region of Gangwon. As the results of spatial analysis, the quaniles have high vaules nearby Seolakdong, Daegwallyeong and Cheongil as the duration of precipitation increase, and the change of spatial distribution occurs severely according to the duration of precipitation. The spatial characteristics of precipitation appears clearly as the return period of quantile increases. As the results of the spatial distribution of precipitation in Gangwon heavy quantiles usually are appeared in Yongdong, and the spatial distributions of quantile in Yongseo are various according to the duration and the return period of quantile. Therefore, to estimate more accurate quantiles in Gangwon, various geographical and weather conditions are considered additionally for the regional precipitation frequency analysis.

• Journal of Korea Society of Waste Management
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• v.35 no.8
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• pp.777-784
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• 2018

Since climate change increases the risk of extreme rainfall events, concerns on flood management have also increased. In order to rapidly recover from flood damages and prevent secondary damages, fast collection and treatment of flood debris are necessary. Therefore, a quick and precise estimation of flood debris generation is a crucial procedure in disaster management. Despite the importance of debris estimation, methodologies have not been well established. Given the intrinsic heterogeneity of flood debris from local conditions, a regional-scale model can increase the accuracy of the estimation. The objectives of this study are 1) to identify significant damage variables to predict the flood debris generation, 2) to ascertain the difference in the coefficients, and 3) to evaluate the accuracy of the debris estimation model. The scope of this work is flood events in Ulsan city region during 2008-2016. According to the correlation test and multicollinearity test, the number of damaged buildings, area of damaged cropland, and length of damaged roads were derived as significant parameters. Key parameters seems to be strongly dependent on regional conditions and not only selected parameters but also coefficients in this study were different from those in previous studies. The debris estimation in this study has better accuracy than previous models in nationwide scale. It can be said that the development of a regional-scale flood debris estimation model will enhance the accuracy of the prediction.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.365-365
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• 2021

기후변화로 인하여 발생하는 자연재해는 수많은 인명 및 재산 피해를 일으키며, 그 중에서도 가뭄은 물과 식량의 안보를 위협하고 있다. 이에 OECD(2015)는 미래의 세계 인구 40%가 2050년까지 물이 부족한 강 유역에서 살 것이라 예측하고 있으며, 물의 다층적 거버넌스를 개발하여 물을 효과적으로 사용하기 위한 상향식 의사결정, 통합물관리 체제의 개념을 제시하기도 하였다. 우리나라 역시 가뭄으로 인한 피해발생이 빈번하고, 그 강도나 범위가 점차 증가하는 추세이다. 하지만 2000년부터 한국농어촌공사(출범은 '농업기반공사')가 농업용수를 관리해오고 있으며, 농업용 수리시설의 증축, 관리 등이 공적인 관리쳬계로 변화해오면서 자연스럽게 농업인의 물관리는 배제되었다. 또한, 농업용수는 무상·무제한 공공재라는 인식과 농업인 평균 연령이 높아짐에 따라 농업인의 물꼬관리 및 수로 훼손, 무단취수 행위 등에 대한 제제가 불가능한 실정이다. 본 연구에서 최근 농식품부의 「2019년 정부가뭄종합대책」에 포함되어 있는 물절약 거버넌스 구축 및 운영 내용을 바탕으로 농업용수 관리 및 사용구조를 고려하여 두 개 지역의 농어촌공사(여주이천지사, 경주지사) 주도 하에 거버넌스를 간담회 형식으로 운영하였다. 농업용수 물절약 거번넌스 이해관계자들은 각 지역별 공기업, 공무원, 농업인, 언론인, 학계 전문가 등이 참가하였으며, 거버넌스 운영 2회 및 설문조사를 실시하였다. 그 결과 각 이해관계자들은 농업용수 절약을 위한 현재 문제점 및 해결방안 등에 대한 의견을 제시하였으며, 설문조사를 통하여 농어촌공사의 신뢰도 및 중요도가 가장 높고, 높은 중요도에 비하여 농업인 및 지자체 등은 신뢰도가 낮은 것을 확인 할 수 있었다. 이러한 결과는 농업인이 농업용수에 대한 주인의식을 가지고, 적극적이고 자발적인 참여가 필요하다는 것을 보여주고 있으며, 본 연구를 통하여 이루어진 간담회 형식의 거버넌스보다 운영효과 및 지속성을 유지할 수 있는 형태의 거버넌스가 연구되어야한다. 향후 농촌형물 거버넌스 모형이 개발되기 위하여 본 연구는 기초자료로 활용할 수 있다.