• 대한토목학회논문집
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• 제34권4호
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• pp.1125-1138
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• 2014

본 연구는 광동댐 유역을 대상으로 RCPs (Representative Concentration Pathways) 기후변화 시나리오의 Arc-SWAT 적용으로 평균유출량과 저유량 계열을 구축하고 경계핵함수(Boundary Kernel)를 이용하여 비매개변수적 갈수빈도 해석을 수행하였다. 분석결과, RCPs 시나리오 하에서 가까운 미래의 유출량 감소로 인한 가뭄발생빈도가 증가하였으며, RCP8.5에서 저유량 계열의 변동폭이 크게 나타났다. Median flow의 갈수량 빈도해석결과 가까운 미래(2030s)의 30년 빈도 갈수량의 경우 Historic 기간에 비하여 증가(RCP4.5: +22.4%, RCP8.5: +40.4%)하였으나, 먼 미래(2080s)에는 갈수량 감소(RCP4.5: -4.7%, RCP8.5: -52.9%)로 인한 가뭄발생빈도가 커지는 것으로 분석되었다. 또한 Quantile 25% flow 저유량 계열의 경우 먼 미래에 빈도별 갈수량이 감소(RCP4.5: -20.8% ~ -60.0%, RCP8.5: -30.4% ~ -96.0%)하여 극심한 가뭄의 발생빈도가 커질 것으로 분석되었다. RCPs 시나리오 적용에 따른 비매개변수적 갈수빈도 해석 결과는 한반도 중권역별 수자원개발계획 수립과 기후변화 대응책 마련을 위한 기초자료로 활용이 가능할 것이다.

• 환경생물
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• 제40권1호
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• pp.1-10
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• 2022

기후변화로 인한 지구온난화는 강수량과 기온에 영향을 주며, 다양한 종들의 서식지와 생물다양성에 상당한 영향을 줄 수 있다. 최근 국제 교류의 증가와 기후변화 등의 원인으로 국내로 새롭게 유입되어 정착하는 외래식물이 증가하고 있지만, 기후변화가 이들 외래식물의 국내 분포에 어떤 영향을 주는지에 대한 연구는 부족한 실정이다. 본 연구는 침입외래식물 큰망초(C. sumatrensis)의 현재 분포와 생물기후 변수를 활용하여 RCPs 기후변화 시나리오에 따른 적합 서식지 분포 변화를 예측하였다. 큰망초는 현재 우리나라 남부 지방에서 제한된 분포를 보이고 있으며, 이들의 분포에는 가장 건조한 분기의 평균기온(bio09), 가장 더운 달의 최고기온(bio05), 등온선(bio03)이 영향을 미치는 것으로 나타났다. 기후변화 시나리오에 따라 큰망초의 미래 적합 서식지 면적은 증가할 것으로 전망되었다. 큰망초와 같은 침입외래종의 분포 변화는 자생식물의 생존을 위협할 수 있으며 생태계 교란을 일으킬 수 있다. 따라서 기후변화에 따른 외래종 분포에 대한 연구는 자생식물뿐만 아니라 생물다양성 보전에 중요한 데이터로 활용될 수 있으며, 향후 서식지 복원과 생물자원을 관리하기 위한 정책자료로 활용될 수 있다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.143-143
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• 2021

Climate change indicators, mainly frequent drought which has happened since the drought of 1994, 1995, and 2012 causing the devastating effect to the agricultural sector, and could be more disruptive given the context of climate change indicators by increasing the temperature and more variable and extreme precipitation. Changes in frequency, duration, and severity of droughts will have enormous impacts on agriculture production and water management. Since both the possibility of drought manifestation and substantial yield losses, we are propositioning an integrated method for evaluating past and future agriculture drought hazards that depend on models' simulations in the Hung-up watershed. to discuss the question of how climate change might influence the impact of extreme agriculture drought by assessing the potential changes in temporal trends of agriculture drought. we will calculate the temporal trends of future drought through drought indices Standardized Precipitation Evapotranspiration Index, Standardized Precipitation Index, and Palmer drought severity index by using observed data of (1991-2020) from Wonju meteorological station and projected climate change scenarios (2021-2100) of the Representative Concentration Pathways models (RCPs). expected results confirmed the frequency of extreme agricultural drought in the future projected to increase under all studied RCPs. at present 100 years drought is anticipated to happen since the result showing under RCP2.6 will occur every 24 years, RCP4.5 every 17 years, and RCPs8.5 every 7 years, and it would be double in the largest warming scenarios. On another side, the result shows unsupportable water management, could cause devastating consequences in both food production and water supply in extreme events. Because significant increases in the drought magnitude and severity like to be initiate at different time scales for each drought indicator. Based on the expected result that the evaluating the impacts of extreme agricultural droughts and recession could be used for the development of proactive drought risk management, policies for future water balance, prioritize sustainable strengthening and mitigation strategies.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.151-151
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• 2018

The present study is aimed to quantifying the uncertainty in the general circulation model (GCM) selection and its impacts on hydrology studies in the basins. For this reason, 13 GCMs was selected among the 26 GCM models of the Fifth Assessment Report (AR5) scenarios. Then, the climate data and hydrologic data with two Representative Concentration Pathways (RCPs) of the best model (INMCM4) and worst model (HadGEM2-AO) were compared to understand the uncertainty associated with GCM models. In order to project the runoff, the Precipitation-Runoff Modelling System (PRMS) was driven to simulate daily river discharge by using daily precipitation, maximum and minimum temperature as inputs of this model. For simulating the discharge, the model has been calibrated and validated for daily data. Root mean square error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were applied as evaluation criteria. Then parameters of the model were applied for the periods 2011-2040, and 2070-2099 to project the future discharge the five large basins of South Korea. Then, uncertainty caused by projected temperature, precipitation and runoff changes were compared in seasonal and annual time scale for two future periods and RCPs compared to the reference period (1976-2005). The findings of this study indicated that more caution will be needed for selecting the GCMs and using the results of the climate change analysis.

• 대기
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• 제23권4호
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• pp.367-375
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• 2013

We present here the future changes in vertical distribution of temperature and tropopause height using the HadGEM2-AO climate model forced with Representative Concentration Pathways (RCPs) scenarios. Projected changes during the 21st century are shown as differences from the baseline period (1971~2000) for global vertical distribution of temperature and tropopause height. All RCP scenarios show warming throughout the troposphere and cooling in the stratosphere with amplified warming over the lower troposphere in the Northern Hemisphere high latitudes. Upper troposphere warming reaches a maximum in the tropics at the 300 hPa level associated with lapse-rate feedback. Also, the cooling in the stratosphere and the warming in the troposphere raises the height of the tropopause.

• 한국농공학회논문집
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• 제54권5호
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• pp.35-41
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• 2012

The paddy rice consumptive use in the six plains of the Korean peninsula was projected with changing climate under the representative concentration pathway (RCP) scenarios. High resolution climate data for the baseline (1961-1990) was obtained from the International water management institute (IWMI) and future high resolution climate projection was obtained from the Korea Meteorological Administration. Reference evapotranspiration (ET) was calculated by using Hargreaves equation. The results of this study showed that the average annual mean temperature would increase persistently in the future. Temperatures were projected to increase more in RCP8.5 than those in RCP4.5 scenario. The rice consumptive use during the growing period was projected to increase slightly in the 2020s and then more significantly in the 2050s and 2080s. It showed higher values for RCP8.5 than for RCP4.5. The rice consumptive use after transplanting in the study areas would increase by 2.2 %, 5.1 % and 7.2 % for RCP4.5 and 3.0 %, 7.6 %, and 13.3 % for RCP8.5, in the 2020s, 2050s, and 2080s, respectively, from the baseline value of 534 mm. The results demonstrated the effects of climate change on rice consumptive use quite well, and can be used in the future agricultural water planning in the Korean peninsula.

• 한국물환경학회지
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• 제40권3호
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• pp.121-129
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• 2024

Harmful cyanobacterial blooms (HCBs) are caused by the rapid proliferation of cyanobacteria and are believed to be exacerbated by climate change. However, the extent to which HCBs will be stimulated in the future due to increased temperature remains uncertain. This study aims to predict the future occurrence of cyanobacteria in the Nakdong River, which has the highest incidence of HCBs in South Korea, based on temperature rise scenarios. Representative Concentration Pathways (RCPs) were used as the basis for these scenarios. Data-driven model simulations were conducted, and out of the four machine learning techniques tested (multiple linear regression, support vector regressor, decision tree, and random forest), the random forest model was selected for its relatively high prediction accuracy. The random forest model was used to predict the occurrence of cyanobacteria. The results of boxplot and time-series analyses showed that under the worst-case scenario (RCP8.5 (2100)), where temperature increases significantly, cyanobacterial abundance across all study areas was greatly stimulated. The study also found that the frequencies of HCB occurrences exceeding certain thresholds (100,000 and 1,000,000 cells/mL) increased under both the best-case scenario (RCP2.6 (2050)) and worst-case scenario (RCP8.5 (2100)). These findings suggest that the frequency of HCB occurrences surpassing a certain threshold level can serve as a useful diagnostic indicator of vulnerability to temperature increases caused by climate change. Additionally, this study highlights that water bodies currently susceptible to HCBs are likely to become even more vulnerable with climate change compared to those that are currently less susceptible.

• 대기
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• 제25권1호
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• pp.85-97
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• 2015

This study is to investigate future changes in carbon cycle using the HadGEM2-Carbon Cycle simulations driven by $CO_2$ emissions. For experiment, global carbon budget is integrated from the two (8.5/2.6) representative concentration pathways (RCPs) for the period of 1860~2100 by Hadley Centre Global Environmental Model, version 2, Carbon Cycle (Had-GEM2-CC). From 1985 to 2005, total cumulative $CO_2$ amount of anthropogenic emission prescribed as 156 GtC. The amount matches to the observed estimates (CDIAC) over the same period (136 GtC). As $CO_2$ emissions into the atmosphere increase, the similar increasing tendency is found in the simulated atmospheric $CO_2$ concentration and temperature. Atmospheric $CO_2$ concentration in the simulation is projected to be 430 ppm for RCP 2.6 at the end of the twenty-first century and as high as 931 ppm for RCP 8.5. Simulated global mean temperature is expected to rise by $1.6^{\circ}C$ and $3.5^{\circ}C$ for RCP 2.6 and 8.5, respectively. Land and ocean carbon uptakes also increase in proportion to the $CO_2$ emissions of RCPs. The fractions of the amount of $CO_2$ stored in atmosphere, land, and ocean are different in RCP 8.5 and 2.6. Further study is needed for reducing the simulation uncertainty based on multiple model simulations.

• Journal of Ecology and Environment
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• 제43권4호
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• pp.427-437
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• 2019

Background: Climate change is believed to be continuously affecting ticks by influencing their habitat suitability. However, we attempted to model the climate change-induced impacts on future genus Rhipicephalus distribution considering the major environmental factors that would influence the tick. Therefore, 50 tick occuance points were taken to model the potential distribution using maximum entropy (MaxEnt) software and 19 climatic variables, taking into account the ability for future climatic change under representative concentration pathways (RCPs) 4.5 and 8.5, were used. Results: MaxEnt model performance was tested and found with the AUC value of 0.99 which indicates excellent goodness-of-fit and predictive accuracy. Current models predict increased temperatures, both in the mid and end terms together with possible changes of other climatic factors like precipitation which may lead to higher tick-borne disease risks associated with expansion of the range of the targeted tick distribution. Distribution maps were constructed for the current, 2050, and 2070 for the two greenhouse gas scenarios and the most dramatic scenario; RCP 8.5 produced the highest increase probable distribution range. Conclusions: The future potential distribution of the genus Rhipicephalus show potential expansion to the new areas due to the future climatic suitability increase. These results indicate that the genus population of the targeted tick could emerge in areas in which they are currently lacking; increased incidence of tick-borne diseases poses further risk which can affect cattle production and productivity, thereby affecting the livelihood of smallholding farmers. Therefore, it is recommended to implement climate change adaptation practices to minimize the impacts.

• 한국환경복원기술학회지
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• 제19권6호
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• pp.19-30
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• 2016

The projection of climate-related range shift is critical information for conservation planning of Korean fir (Abies koreana E. H. Wilson). We first modeled the distribution of Korean fir under current climate condition using five single-model species distribution models (SDMs) and the pre-evaluation weighted ensemble method and then predicted the distributions under future climate conditions projected with HadGEM2-AO under four $CO_2$ emission scenarios, the Representative Concentration Pathways (RCP) 2.6, 4.5, 6.0 and 8.5. We also investigated the predictive uncertainty stemming from five individual algorithms and four $CO_2$ emission scenarios for better interpretation of SDM projections. Five individual algorithms were Generalized linear model (GLM), Generalized additive model (GAM), Multivariate adaptive regression splines (MARS), Generalized boosted model (GBM) and Random forest (RF). The results showed high variations of model performances among individual SDMs and the wide range of diverging predictions of future distributions of Korean fir in response to RCPs. The ensemble model presented the highest predictive accuracy (TSS = 0.97, AUC = 0.99) and predicted that the climate habitat suitability of Korean fir would increase under climate changes. Accordingly, the fir distribution could expand under future climate conditions. Increasing precipitation may account for increases in the distribution of Korean fir. Increasing precipitation compensates the negative effects of increasing temperature. However, the future distribution of Korean fir is also affected by other ecological processes, such as interactions with co-existing species, adaptation and dispersal limitation, and other environmental factors, such as extreme weather events and land-use changes. Therefore, we need further ecological research and to develop mechanistic and process-based distribution models for improving the predictive accuracy.