• Journal of the Geological Society of Korea
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• v.54 no.5
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• pp.545-556
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• 2018

This study was conducted to estimate the deep percolation using numerical modeling and field observation data based on rainfall in Haean basin. Soil moisture sensors were installed to monitoring at 30, 60 and 90 cm depths in four sites (YHS1-4) and automatic weather station was installed to around YHS3. Soil moisture and meteorological data was observed from March 25, 2017 to March 25, 2018 and May 06, 2016 to May 06, 2018, respectively. Numerical analysis was performed from June to August, 2017 using the HYDRUS-1D. Average soil moisture contents were high to generally in YHS3 for 0.300 to $0.334m^3/m^3$ and lowest in YHS1 for 0.129 to $0.265m^3/m^3$ during the soil moisture monitoring period. The results of soil moisture flow modeling showed that field observations and modeling values were similar but the peak values were larger in the modeling result. Correlation analysis between observation and modeling data showed that r, $r^2$ and RMSE were 0.88, 0.77, and 0.0096, respectively. This show high correlation and low error rate. The total deep percolation was 744.2 mm during the period of modelling at 500 cm depth. This showed that 61.3% of the precipitation amount (1,214 mm) was recharged in 2017. Deep percolation amount was high in the study area. This study is expected to provide basic data for the estimation of groundwater recharge through unsaturated zone.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.434-439
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• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• Journal of Korea Water Resources Association
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• v.55 no.3
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• pp.205-215
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• 2022

Amidst the global climate crisis, dam operation policies formulated under the stationary climate assumption could lead to unsatisfactory water management. In this work, we assessed status-quo performance of the Yongdam Dam in Korea under various climatic stresses in flood risk reduction and water supply reliability for 2021-2040. To this end, we employed a decision-centric framework equipped with a stochastic weather generator, a conceptual streamflow model, and a machine-learning reservoir operation rule. By imposing 294 climate perturbations to dam release simulations, we found that the current operation rule of the Yongdam dam could redundantly secure water storage, while inefficiently enhancing the supply reliability. On the other hand, flood risks were likely to increase substantially due to rising mean and variability of daily precipitation. Here, we argue that the current operation rules of the Yongdam Dam seem to be overly focused on securing water storage, and thus need to be adjusted to efficiently improve supply reliability and reduce flood risks in downstream areas.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.969-983
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• 2021

Evapotranspiration, one of the hydrometeorological components, is considered an important variable for water resource planning and management and is primarily used as input data for hydrological models such as water balance models. The FAO56 PM method has been recommended as a standard approach to estimate the reference evapotranspiration with relatively high accuracy. However, the FAO56 PM method is often challenging to apply because it requires considerable hydrometeorological variables. In this perspective, the Hargreaves equation has been widely adopted to estimate the reference evapotranspiration. In this study, a set of parameters of the Hargreaves equation was calibrated with relatively long-term data within a Bayesian framework. Statistical index (CC, RMSE, IoA) is used to validate the model. RMSE for monthly results reduced from 7.94 ~ 24.91 mm/month to 7.94 ~ 24.91 mm/month for the validation period. The results confirmed that the accuracy was significantly improved compared to the existing Hargreaves equation. Further, the evaporative demand drought index (EDDI) based on the evaporative demand (E₀) was proposed. To confirm the effectiveness of the EDDI, this study evaluated the estimated EDDI for the recent drought events from 2014 to 2015 and 2018, along with precipitation and SPI. As a result of the evaluation of the Han-river watershed in 2018, the weekly EDDI increased to more than 2 and it was confirmed that EDDI more effectively detects the onset of drought caused by heatwaves. EDDI can be used as a drought index, particularly for heatwave-driven flash drought monitoring and along with SPI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.617-626
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• 2022

In Korea, annual precipitation and its variability have gradually increased since modern meteorological observations began, and the risk of disasters has also been increasing due to significant regional variations and recent abnormal climate conditions. Given that damage from storms and floods mainly occurs around rivers, it is crucial to determine the appropriate design frequency for river-related projects. This study examined existing design practices used to determine hydrological design frequencies and suggested a new method to determine appropriate design frequencies. The study collected available data pertaining to seven evaluation factors, specifically the basin areas, shape parameters, channel slopes, stream orders, backwater effect reaches, extreme rainfall frequencies, and urbanized flood inundation areasfor 413 local rivers in Chungcheongnam-do in Korea. The estimated weights for areas of extreme rainfall frequencies and urbanized flood inundation were found to be 18, having a great effect on determining the design frequency. Compared with the established design frequency in previous government reports, the estimated design frequency increased for 255 rivers and decreased for 158 rivers.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1119-1130
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• 2021

Urban flooding caused by localized heavy rainfall with unstable climate is constantly occurring, but a system that can predict spatial flood information with weather forecast has not been prepared yet. The worst flood situation in urban area can be occurred with difficulties of structural measures such as river levees, discharge capacity of urban sewage, storage basin of storm water, and pump facilities. However, identifying in advance the spatial flood information can have a decisive effect on minimizing flood damage. Therefore, this study presents a methodology that can predict the urban flood map in real-time by using rainfall data of the Korea Meteorological Administration (KMA), the results of two-dimensional flood analysis and random forest (RF) regression model. The Ujeong district in Ulsan metropolitan city, which the flood is frequently occurred, was selected for the study area. The RF regression model predicted the flood map corresponding to the 50 mm, 80 mm, and 110 mm rainfall events with 6-hours duration. And, the predicted results showed 63%, 80%, and 67% goodness of fit compared to the results of two-dimensional flood analysis model. It is judged that the suggested results of this study can be utilized as basic data for evacuation and response to urban flooding that occurs suddenly.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.30-40
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• 2022

Wildfires, which occur sporadically and irregularly worldwide, are distinct natural disturbances in combustible vegetation areas, important parts of the global carbon cycle, and natural disasters that cause severe public emergencies. While many previous studies have investigated the variability and changes in wildfires globally based on fire emissions, burned areas, and fire weather indices, studies on East Asia are still limited. Here, we explore the characteristics of variability and changes in wildfire danger over East Asia by analyzing the fire weather index for the 40 years-1981-2020. The first empirical orthogonal function (EOF) mode of fire weather index variability represents an increasing trend in wildfire danger over most parts of East Asia over the last 40 years, accounting for 29% of the total variance. The major contributor is an increase in the surface temperature in East Asia associated with global warming and multidecadal ocean variations. The effect of temperature was slightly offset by the increase in soil moisture. The second EOF mode exhibits considerable interannual variability associated with the El Nino-Southern Oscillation, accounting for 17% of the total variance. The increase (decrease) in precipitation in East Asia during El Nino (La Nina) increases (decreases) soil moisture, which in turn reduces (increases) wildfire danger. This dominant soil moisture effect was slightly offset by the temperature increase (decrease) during El Nino (La Nina). Improving the understanding of variability and changes in wildfire danger will have important implications for reducing social, economic, and ecological losses associated with wildfire occurrences.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.316-316
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• 2023

2022년 8월 수도권 이상폭우로 인해 서울 도심지역의 지하시설, 도로, 주택 등에 침수가 발생하면서 인명 및 재산피해가 발생하였으며, 특히 동서로 가로지르는 정체전선으로 좁고 긴 비구름이 집중되면서 국지적으로 피해가 집중되었다. 서울시의 경우 도시화에 따른 불투수지역 증가 및 내수배제 불량에 따른 빗물 역류로 인한 피해가 지속적으로 발생하고 있으며, 최근에는 기후변화에 따른 방재성능목표 강우량을 초과하는 빈도의 이상폭우로 인해 하천범람과 내수배제 불량에 따른 복합적인 원인으로 침수피해 가중되고 있는 실정이다. 또한 서울시의 경우 전체 자연적, 사회적, 경제적, 환경적 요인 등의 지역적 편차가 매우 큰 도시로 지형적인 특성뿐만 아니라 취약시설(병원, 학교 등), 수방시설물(하천, 배수시설, 빗물펌프장 등) 및 방재시설(대피소, 구호소 등) 밀도 등에 따른 침수 취약성 및 위험성 등의 편차가 매우 크기 때문에 지역특성에 대한 피해사례가 다원화 되고 있는 실정이다. 본 연구에서는 30년 이상의 종관기상관측(ASOS)과 서울시 자치구별 20년 이상의 방재기상관측(AWS)자료를 기반으로 CMIP6 SSP(Shared Socioeconomic Pathways, 공통사회 경제경로)시나리오에 따른 극한기후 지수(강수강도, 호우일수, 지속기간, 1일 최대강수량, 95퍼센타일 강수일수 등)에 대한 재현성을 평가하고 공간자기상관분석 등 시공간적인 강우특성에 대한 변화를 전망하였다. 특히 여름철 강우의 경우 자치구별 편차가 크게 나타났고 이를 통해 대도시의 도심지역의 경우 세분화하여 지역의 정확한 강우특성을 파악하는 것이 필요하다는 것을 확인할 수 있었다. 본 연구의 결과는 도심지의 방재성능 초과강우 정의와 기준을 수립하고, 장기적인 수자원 및 도시계획 차원의 대책을 마련하는데 활용될 수 있을 것으로 판단된다. 기후위기에 따른 기록적인 호우(지역별 방재성능을 초과하는 강우)에 따른 재해는 구조적인 대책을 통해 모두 저감할 수 없는 한계가 있다. 하지만 인명피해를 최소화하는 것을 목표로 기후위기에 대한 적응단계로 인식하고 수리·수문학적, 사회경제학적 등 지역특성에 따른 방재성능목표 강우량에 대한 재검토와 더불어 법제도(풍수해보험, 저류조설치 의무화 등), 개인별 재해예방, 취약계층 안전망 확보, 반지하주택 침수안전대책, 재해지도 개선 등 구조적/비구조적인 대책을 통합 수립 및 보완하는 것이 필요한 시점이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.31-31
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• 2022

기후변화, 물 부족, 인구 증가와 도시화로 인한 물 수요 증가, 수질 악화, 노후화된 인프라와 같은 세계적인 물문제의 증가로 인해, 도시 물순환 시스템 관리는 더 큰 어려움을 겪고 있다. 취수, 도·송수, 정수처리, 배·급수, 용수 사용, 하수 집수, 하수 처리, 재이용 및 배출 과정을 포함하는 도시 물순환 시스템의 과정은 매우 에너지 집약적인 활동이며, 이와 같은 에너지 소비는 탄소 배출과 양의 직접적인 상관관계가 있다. 따라서 자원 관리 및 데이터 관리를 최적화하기 위해 넥서스 관점의 접근법이 도시 물순환 시스템에 점차적으로 도입되고 있는 추세이다. 도시 물순환 시스템 넥서스에서는 일반적으로 에너지 인텐시티로 표현되는 물을 위한 에너지를 이해하는 것이 중요하다. 에너지 인텐시티의 차이는 기후(연평균 강수량, 단기 기후 변동성, 기후패턴 등), 지리적 특징(표고차, 평지비, 위치 등), 시스템 특성(총급수량, 인구, 인구밀도, 관로 연장 등) 및 운영관리 효율(수압, 누수율, 에너지 효율 등)과 밀접한 관계가 있다. 그리고 도시 물순환 시스템에서 에너지 관리를 증진시킨 방안은 유지관리 효율 개선(물·에너지 관리전략, 물손실 관리, 수요 관리 및 수요 대응 등), 신기술 도입, 그리고 에너지 회수로 나누어진다. 본 연구에서는 기존 문헌의 자료를 분석하여 도시 물순환 시스템의 각 공정별 에너지 인텐시티를 분석하였으며, 시스템 다이나믹스를 적용하여 다양한 도시 여건(인구, lpcd, 누수율, 취수원, 에너지 인텐시티)에서 외부영향(기후변화, 도시화)과 운영효율 변동(운영효율 향상, 신시술 도입)에 따른 도시 물순환 시스템 내 자원 사용 및 이동을 분석하였다. 에너지 인텐시티는 전체 도시 물순환 시스템, 상수 시스템, 하수시스템에서 각각 2.334 kWh/m³, 1.029 kWh/m³, 1.024 kWh/m³를 나타내었으며, 용수사용, 담수화, 재이용 과정에서는 매우 높은 값이 나타났다. 에너지 인틴시티의 값은 외부 영향에 크게 좌우되는 것으로 분석되었으며, 운영효율의 변동에 따라서 물 및 에너지 사용량은 변화하였지만 에너지 인텐시티의 변동은 크지 않았다. 이에 따라 도시 물순환 시스템을 넥서스 관점에서 관리하기 위해서는 에너지 인텐시티 이외에 물 및 에너지 사용량, 유수수량 관점 에너지 인텐시티, 사용수량 관점 에너지 인텐시티를 종합적으로 고려하는 것이 필요하다.

• Korean Journal of Environmental Biology
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• v.40 no.1
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• pp.1-10
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• 2022

Global warming has a major impact on the Earth's precipitation and temperature fluctuations, and significantly affects the habitats and biodiversity of many species. Although the number of alien plants newly introduced in South Korea has recently increased due to the increasing frequency of international exchanges and climate change, studies on how climate change affects the distribution of these alien plants are lacking. This study predicts changes in the distribution of suitable habitats according to RCPs climate change scenarios using the current distribution of the invasive alien plant Conyza sumatrensis and bioclimatic variables. C. sumatrensis has a limited distribution in the southern part of South Korea. Isothermality (bio03), the max temperature of the warmest month (bio05), and the mean temperature of the driest quarter (bio09) were found to influence the distribution of C. sumatrensis. In the future, the suitable habitat for C. sumatrensis is projected to increase under RCP 4.5 and RCP 8.5 climate change scenarios. Changes in the distribution of alien plants can have a significant impact on the survival of native plants and cause ecosystem disturbance. Therefore, studies on changing distribution of invasive species according to climate change scenarios can provide useful information required to plan conservation strategies and restoration plans for various ecosystems.