• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.42-42
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• 2023

최근 IPCC 6차 보고서에서는 전 지구의 온도가 0.5℃가 증가할 때마다 기상학적 가뭄 지역이 증가하며, 인위적 강제력은 가뭄 현상의 강도와 빈도를 증가하는 것으로 밝혔다. 봄철(3월-5월) 동남아시아(남중국, 필리핀 등)에 비해 상대적으로 건조한 동북아시아(동중국, 한반도, 일본) 지역은 가뭄에 취약하며 기후 변화에 따라 가뭄으로 인한 피해가 커질 것으로 전망된다. 그러므로 이 지역은 봄철 가뭄으로 인한 피해를 완화하기 위해 봄철 강수량에 대한 신뢰할 만한 계절적 예보 기술이 꼭 필요하다. 본 연구에서는 1992-2022년 봄철의 Standardized Precipitation Index(SPI) 값을 기준으로 2001년과 2011년 동북아시아 가뭄이 발생한 것을 확인하였으며, 각 해의 3월에 관측된 기상학적 초기 조건으로부터 다중 기후 예보 모델들의 봄철 강수량의 계절적 예측성을 정량적으로 평가하였다. 관측자료로부터 2001년 가뭄은 동북아시아 대기 상층의 저기압성 순환의 강화로 인한 제트류(Jet stream)의 강화와 연관되어 있었으며, 2011년 가뭄은 제트류 강화와 함께 태평양 열대 지역 기류 강화가 동반되어 발생하였음을 알 수 있었다. North American Multi-Model Ensemble 기후 예보 모델들은 2011년 가뭄에 비해 2001년 가뭄에 대한 예측성이 높았으며, 그 이유로는 대기 상층 순환의 예측성과 연관이 있음을 밝혔다. 또한, 봄철 대기-해양 상호 패턴을 관측과 유사하게 재현한 GFDL-SPEARS 모델이 가뭄 해의 대기 상층 저기압성 순환과 강수 예측성이 가장 높은 것을 보였다. 본 연구의 결과들을 통해 동북아시아 봄철 가뭄과 같은 극한 기상의 강수량 예측성 향상에 있어서 기후 예보 모델들의 현실적인 대기-해양 결합 과정 모사 능력의 중요성을 밝혔다. 본 연구에서 제안된 방안들은 기후 예측 모델 개선을 위한 전략적인 정보를 제공할 것으로 보인다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.43-43
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• 2020

보령댐은 충남 서부지역 8개 시·군에 생활용수와 공업용수를 공급하고 있는 중요한 수원으로 최근 우리나라에서 발생한 연속적인 가뭄으로 2015년에는 저수율이 7.5 %까지 감소하여 제한급수가 시행되었다. 본 연구에서는 가뭄으로 인한 물 공급 부족에 취약함을 보인 보령댐 유역(297.4 ㎢)을 대상으로 SWAT(Soil and Water Assessment Tool) 모델과 RCP(Representative Concentration Pathways) 시나리오를 활용하여 극한 기후변화 사상이 반영된 보령댐의 내한능력을 평가하였다. SWAT 모형을 활용하여 보령댐의 물수지를 모의하기 위하여 보령댐의 실측 유출량, 저수량, 방류량으로 보령댐 유입량과 저수량을 보정(2002~2004) 및 검정(2005~2007)하였으며, 실측 저수량을 기반으로 미래 댐 운영을 모의하였다. 검·보정 결과, 댐 유입량과 저수량의 PBIAS(%)는 -0.04, -0.09, NSE(Nash and Sutcliffe Efficiency)는 0.52, 0.96, RMSE(Root Mean Square Error)는 1.80 mm/day, 0.67 × 10⁶㎥로 분석되어 신뢰성 있는 모의 결과를 보였다. 보정된 SWAT 모형으로 가뭄 사상이 반영된 기후변화를 모의하기 위하여 APCC의 26개 CMIP5 GCM 시나리오를 SPI (Standardized Precipitation Index)와 연속 이론(Runs theory)으로 분석하여 6개의 극한 가뭄 시나리오 (RCP 4.5, 8.5 CMCC-CM, INM-CM4, IPSL-CM5A-MR)를 선정하였으며, 선정된 시나리오를 모형에 적용하여 가뭄 사상을 반영한 보령댐의 미래 내한능력을 평가하였다. 내한능력평가 및 분석 기간은 Historical(1980~1999; 1990s), Present(2000~2019; 2010s), 그리고 미래 기간 (2020~2039; 2030s, 2040~2059; 2050s, 2060~2079; 2070s, 2080~2099; 2090s)으로 나누었으며, 취약성(Reliability), 회복성(Resilience), 위험성(Vulnerability), 세 가지 지표로 내한능력 평가를 수행하였다. 평가 결과, 미래 취약성은 2050s IPSL-CM5A-MR 시나리오에서 0.803까지 감소하였으며, 회복성과 위험성은 2070s IPSL-CM5A-MR 시나리오에서 0.003, 3,567.6 × 10⁶㎥까지 감소하였다.

• Clinical and Experimental Vaccine Research
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• v.12 no.2
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• pp.156-171
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• 2023

Purpose: The development of vaccines that confer protection against multiple avian influenza A (AIA) virus strains is necessary to prevent the emergence of highly infectious strains that may result in more severe outbreaks. Thus, this study applied reverse vaccinology approach in strategically constructing messenger RNA (mRNA) vaccine construct against avian influenza A (mVAIA) to induce cross-protection while targeting diverse AIA virulence factors. Materials and Methods: Immunoinformatics tools and databases were utilized to identify conserved experimentally validated AIA epitopes. CD8⁺ epitopes were docked with dominant chicken major histocompatibility complexes (MHCs) to evaluate complex formation. Conserved epitopes were adjoined in the optimized mVAIA sequence for efficient expression in Gallus gallus. Signal sequence for targeted secretory expression was included. Physicochemical properties, antigenicity, toxicity, and potential cross-reactivity were assessed. The tertiary structure of its protein sequence was modeled and validated in silico to investigate the accessibility of adjoined B-cell epitope. Potential immune responses were also simulated in C-ImmSim. Results: Eighteen experimentally validated epitopes were found conserved (Shannon index <2.0) in the study. These include one B-cell (SLLTEVETPIRNEWGCR) and 17 CD8⁺ epitopes, adjoined in a single mRNA construct. The CD8⁺ epitopes docked favorably with MHC peptidebinding groove, which were further supported by the acceptable ∆G_bind (-28.45 to -40.59 kJ/mol) and Kd (<1.00) values. The incorporated Sec/SPI (secretory/signal peptidase I) cleavage site was also recognized with a high probability (0.964814). Adjoined B-cell epitope was found within the disordered and accessible regions of the vaccine. Immune simulation results projected cytokine production, lymphocyte activation, and memory cell generation after the 1st dose of mVAIA. Conclusion: Results suggest that mVAIA possesses stability, safety, and immunogenicity. In vitro and in vivo confirmation in subsequent studies are anticipated.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.61-89
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• 2020

The objective of this study is to characterize landslide susceptibility depending on various geo-environmental variables as well as to compare the Frequency Ratio (FR) and Evidential Belief Function (EBF) methods for landslide susceptibility analysis of rainfall-induced landslides. In 2013, a total of 259 landslides occurred in Chuncheon, Gangwon Province, South Korea, due to heavy rainfall events with a total cumulative rainfall of 296~721mm in 106~231 hours duration. Landslides data were mapped with better accuracy using the geographic information system (ArcGIS 10.6 version) based on the historic landslide records in Chuncheon from the National Disaster Management System (NDMS), the 2013 landslide investigation report, orthographic images, and aerial photographs. Then the landslides were randomly split into a testing dataset (70%; 181 landslides) and validation dataset (30%; 78 landslides). First, geo-environmental variables were analyzed by using FR and EBF functions for the full data. The most significant factors related to landslides were altitude (100~200m), slope (15~25°), concave plan curvature, high SPI, young timber age, loose timber density, small timber diameter, artificial forests, coniferous forests, soil depth (50~100cm), very well-drained area, sandy loam soil and so on. Second, the landslide susceptibility index was calculated by using selected geo-environmental variables. The model fit and prediction performance were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under Curve (AUC) methods. The AUC values of both model fit and prediction performance were 80.5% and 76.3% for FR and 76.6% and 74.9% for EBF respectively. However, the landslide susceptibility index, with classes of 'very high' and 'high', was detected by 73.1% of landslides in the EBF model rather than the FR model (66.7%). Therefore, the EBF can be a promising method for spatial prediction of landslide occurrence, while the FR is still a powerful method for the landslide susceptibility mapping.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.481-491
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• 2024

Recent droughts make hydroelectric power generation (HPG) decreasing. Due to climate change in the future, the frequency and intensity of drought are expected to increase, which will increase uncertainty of HPG in multi-purpose dams. Therefore, it is necessary to estimate the amount of HPG according to climate change scenarios and analyze the effect of drought on the amount of HPG. This study analyzed the future HPG of the Soyanggang Dam and Chungju Dam according to the SSP2-4.5 and SSP5-8.5 scenarios. Regression equations for HPG were developed based on the observed data of power generation discharge and HPG in the past provided by My Water, and future HPGs were estimated according to the SSP scenarios. The effect of drought on the amount of HPG was investigated based on the drought severity calculated using the standardized precipitation index (SPI). In this study, the future SPIs were calculated using precipitation data based on four GCM models (CanESM5, ACCESS-ESM1-5, INM-CM4-8, IPSL-CM6A) provided through the environmental big data platform. Overall results show that climate change had significant effects on the amount of HPG. In the case of Soyanggang Dam, the amount of HPG decreased in the SSP2-4.5 and SSP5-8.5 scenarios. Under the SSP2-4.5 scenario the CanESM model showed a 65% reduction in 2031, and under the SSP5-8.5 scenario the ACCESS-ESM1-5 model showed a 54% reduction in 2029. In the case of Chungju Dam, under the SSP2-4.5 and SSP5-8.5 scenarios the average monthly HPG compared to the reference period showed a decreasing trend except for INM-CM4 model.

• Economic and Environmental Geology
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• v.50 no.2
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• pp.129-143
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• 2017

The shallow sediments in the southwestern Ulleung Basin consist of mass flow deposits such as slide/slump and debris flow deposits (DFD), caused by slope failure. These sediments are proven to be important in studying geological disaster and stability of the seafloor. In this paper, we analysised the flow accumulation and slope failure susceptibility of the Ulleung Basin on the basis of multi-beam data, collected in this area. We also studied the distribution pattern and the seismic characteristics of the DFD in the uppermost layer of the Ulleung Basin on the basis of seismic data. The slope susceptibility was calculated as the frequency ratio of each factors including slope, aspect, curvature and stream power index (SPI), which causes the slope failure. These results indicate that the slope failure is frequently to occur in the southern and western continental slope of the Ulleung Basin. The sediment flow (mass flow) caused by the slope failure converges to the north and northwest of the Ulleung Basin. According to the seismic characteristics, the uppermost layer in study area can be divided into four sedimentary unit. These sedimentary units develop from the south and southwest to the north and northwest in association with slope susceptibility and flow accumulation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.242-252
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• 2016

A process-based ecosystem model, BIOME-BGC, was applied to simulate seasonal and inter-annual dynamics of carbon and water processes for potential evergreen needleleaf forest (ENF) biome in Korea. Two simulation sites, Milyang and Unljin, were selected to reflect warm-and-dry and cool-and-wet climate regimes, where massive diebacks of pines including Pinus densiflora, P. koraiensis and P thunbergii, were observed in 2009 and 2014, respectively. Standard Precipitation Index (SPI) showed periodic drought occurrence at every 5 years or so for both sites. Since mid-2000s, droughts occurred with hotter climate condition. Among many model variables, Cpool (i.e., a temporary carbon pool reserving photosynthetic compounds before allocations for new tissue production) was identified as a useful proxy variable of tree carbon starvation caused by reduction of gross primary production (GPP) and/or increase of maintenance respiration (Rm). Temporal Cpool variation agreed well with timings of pine tree diebacks for both sites. Though water stress was important, winter- and spring-time warmer temperature also played critical roles in reduction of Cpool, especially for the cool-and-wet Uljin. Shallow soil depth intensified the drought effect, which was, however, marginal for soil depth shallower than 0.5 m. Our modeling analysis implicates seasonal drought and warmer climate can intensify vulnerability of ENF dieback in Korea, especially for shallower soils, in which multi-year continued stress is of concern more than short-term episodic stress.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1803-1818
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• 2021

As the frequency of drought increases due to climate change, it is very important to have a monitoring system that can accurately determine the situation of widespread drought. However, while ground-based meteorological data has limitations in identifying all the complex droughts in Korea, satellite remote sensing data can be effectively used to identify the spatial characteristics of drought in a wide range of regions and to detect drought. This study attempted to analyze the possibility of using remote sensing data for drought identification in South Korea. In order to monitor various aspects of drought, remote sensing and ground observation data of precipitation and potential evapotranspiration, which are major variables affecting drought, were collected. The evaluation of the applicability of remote sensing data was conducted focusing on the comparison with the observation data. First, to evaluate the applicability and accuracy of remote sensing data, the correlations with observation data were analyzed, and drought indices of various aspects were calculated using precipitation and potential evapotranspiration for meteorological drought monitoring. Then, to evaluate the drought monitoring ability of remote sensing data, the drought reproducibility of the past was confirmed using the drought index. Finally, a high-resolution drought map using remote sensing data was prepared to evaluate the possibility of using remote sensing data for actual drought in South Korea. Through the application of remote sensing data, it was judged that it would be possible to identify and understand various drought conditions occurring in all regions of South Korea, including unmeasured watersheds in the future.

• Economic and Environmental Geology
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• v.36 no.6
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• pp.457-467
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• 2003

Soil Precise Investigation(SPI) for river deposits and farmland soils around Goro abandoned Zn-mine, Korea was performed to assess the pollution level of heavy metals(As. Pb, Cd, Cu) and to estimate the remediation volume for contaminated soils. Total investigation area was about 950000 $m^2$, which was divided into each section of 1500 $m^2$ corresponding to one sampling site and 545 samples for surface soil(0-10cm in depth) and 192 samples for deep soil(10-30cm in depth) from the investigation area were collected for analysis. Concentrations of Cu, Cd, Pb at all sample sites were shown to be lower than Soil Pollution Warning Limit(SPWL). For arsenic concentration, in surface soils, 20.5% of sample sites(104 sites) were over SPWL(6mg/kg) and 6.7%(34 sites) were over Soil Pollution Counterplan Limit(SPCL: 15mg/kg) suggesting that surface soils were broadly contaminated by As. For deep soils, 10.4% of sample sites(18 sites) were over SPWL and 0.6%(1 site) were over SPCL. Four pollution grades for sample locations were prescribed by the Law of Soil Environmental Preservation and Pollution Index(PI) for each soil sample was decided according to pollution grades(over 15.0 mg/kg, 6.00-15.00 mg/kg, 2.40-6.00 mg/kg, 1.23-6.00 mg/kg). The pollution contour map around Goro mine based on PI results was finally created to calculate the contaminated area and the remediation volume for contaminated soils. Remediation area with over SPWL concentration was about 0.3% of total area between Goro mine and a projected storage dam and 0.9% of total area was over 40% of SPWL. If the remediation target concentration was determined to over background level concentration, 1.1% of total area should be treated for remediation. Total soil volume to be treated for remediation was estimated on the assumption that the thickness of contaminated soil was 30cm. Soil volume to be remediated based on the excess of SPWL was estimated at 79,200$m^3$, soil volume exceeding 40% of SPWL was about 233,700 $m^3$, and soil volume exceeding the background level(1.23 mg/kg) was 290,760 TEX>$m^3$.